Research Scientist jobs at Toyota Research Institute - 22 jobs

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. Within the Human Interactive Driving division, the Extreme Performance Intelligent Control department is working to develop scalable, human-like driving intelligence by learning from expert human drivers. This project focuses on creating a configurable, data-driven world model that serves as a foundation for intelligent, multi-agent reasoning in dynamic driving environments. By tightly integrating advances in perception, world modeling, and model-based reinforcement learning, we aim to overcome the limitations of more compartmentalized, rule-based approaches. The end goal is to enable robust and adaptable, driving policies that generalize across tasks, sensor modalities, and public road scenarios-delivering ground-breaking improvements for ADAS, autonomous systems, and simulation-driven software development. We are seeking a highly motivated Research Scientist specializing in uncertainty-aware world models for autonomous vehicles. In this role, you will develop cutting-edge models that enable autonomous systems to perceive, predict, and interact intelligently with their environment. You will work at the intersection of machine learning, computer vision, robotics, and probabilistic modeling to build robust world models that improve perception, planning, and decision-making in self-driving systems.Responsibilities Develop and refine world models that improve the understanding of sophisticated and dynamic driving environments. Research and implement deep learning, reinforcement learning, and probabilistic modeling techniques for improved scene representation and prediction. Design algorithms that integrate sensor fusion, temporal reasoning, and uncertainty estimation to improve autonomous vehicle behavior. Collaborate with cross-functional teams, including perception, planning, and simulation engineers, to develop real-time, scalable models for deployment. Conduct experiments, simulations, and real-world validations to assess the effectiveness of world models. Publish research findings in premier conferences and journals and contribute to the AI and robotics research community. Stay up to date with advancements in machine learning, generative modeling, and simulation technologies. Qualifications Ph.D. (or equivalent experience) in Machine Learning, Computer Science, Robotics, or a related field. Strong background in probabilistic modeling, reinforcement learning, and deep learning architectures (e.g., Transformers, VAEs, Diffusion Models). Strong understanding of Bayesian inference, state-space models, and uncertainty quantification. Hands-on experience with world models, predictive modeling, or generative modeling in robotics or autonomous systems. Prior experience in publishing research at NeurIPS, ICML, CVPR, ICRA, or similar. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, JAX). Experience working with autonomous vehicle datasets, sensor modalities (LiDAR, camera, radar), and simulation environments. Excellent problem-solving skills and the ability to work in a fast-paced team research environment. Please submit a brief cover letter and add a link to Google Scholar to include a full list of publications when submitting your CV for this position. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. Within the Human Interactive Driving division, the Extreme Performance Intelligent Control department is working to develop scalable, human-like driving intelligence by learning from expert human drivers. This project focuses on creating a configurable, data-driven world model that serves as a foundation for intelligent, multi-agent reasoning in dynamic driving environments. By tightly integrating advances in perception, world modeling, and model-based reinforcement learning, we aim to overcome the limitations of more compartmentalized, rule-based approaches. The end goal is to enable robust, adaptable, and interpretable driving policies that generalize across tasks, sensor modalities, and public road scenarios-delivering ground-breaking improvements for ADAS, autonomous systems, and simulation-driven software development. We are seeking a forward-thinking Research Scientist to focus on inferring latent state representations from sensor data, powering world models, and supporting rigorous policy evaluation for autonomous vehicles. This role spans raw perception and structured representations, enabling both high-fidelity predictive modeling and reliable policy assessment in simulated or learned environments. You will work closely with researchers developing world models and those focused on policy evaluation, ensuring that the latent states inferred from real-world sensors are semantically rich, temporally coherent, and suitable for both long-horizon prediction and counterfactual analysis.Responsibilities Design and train learning-based systems that transform raw multimodal sensor data (e.g., images, lidar, radar) into compact, dynamic latent states suitable for use in learned world models. Investigate unsupervised, self-supervised, and contrastive methods to learn latent spaces that encode dynamics, semantics, and uncertainty. Incorporate temporal information and motion consistency into latent state estimation using recurrent, filtering, or transformer-based architectures. Combine data from heterogeneous modalities into a unified latent state representations that generalize across conditions and scenarios. Ensure the learned representations are resilient to occlusion, sensor degradation, and distributional shift. Collaborate on joint research agendas with world modeling and policy evaluation researchers to explore uncertainty modeling, interpretability, and representation bottlenecks. Publish novel research, contribute to open-source tools, and engage with the academic community at major ML and robotics conferences. Qualifications PhD in Computer Science, Machine Learning, Robotics, or a related field. Strong foundation in representation learning or state estimation for sequential decision-making. Robust experience in deep generative models (e.g., VAEs, diffusion models, autoregressive models). Solid base in perception models from large-scale real-world sensor datasets from autonomous driving, robotics, or similar domains. Experience with latent world models, generative AI for perception, or contrastive learning. Familiarity with structure-from-motion, Gaussian splatting, or neural radiance fields (NeRFs). Experience with multi-modal sensor fusion, state estimation, and SLAM techniques. Familiarity with uncertainty-aware perception, active perception, and predictive modeling. Accomplished publication record at top-tier conferences such as NeurIPS, CVPR, ICCV, ICLR, ICRA, CoRL, or RSS. Deep programming skills in Python and deep learning frameworks such as PyTorch or JAX. Excellent problem-solving skills and the ability to work in a fast-paced team research environment. Bonus Qualifications Background building or using world models in model-based RL, planning, or simulation. Familiarity with latent-space rollouts, policy evaluation metrics, or offline RL tools. Knowledge working in high-dimensional, real-time environments with latency constraints. Please add a link to Google Scholar to include a full list of publications when submitting your CV for this position. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The Mission Make general-purpose robots a reality. The Challenge We envision a future where robots assist with household chores and cooking, aid the elderly in maintaining their independence, and enable people to spend more time on the activities they enjoy most. To achieve this, robots must be able to operate reliably in complex, unstructured environments. Our mission is to answer the question “What will it take to create truly general-purpose robots that can accomplish a wide variety of tasks in settings like human homes with minimal human supervision?” We believe that the answer lies in cultivating large-scale datasets of physical interaction from a variety of sources and building on the latest advances in machine learning to learn general purpose robot behaviors from this data. The Team The Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc.) data from multiple domains (driving, robotics, indoors, outdoors, etc.) to improve the performance of downstream tasks. This paradigm targets training scalability, since data from multiple modalities can be equally leveraged to learn useful data-driven priors (3D geometry, physics, dynamics, etc) for world understanding. Our topics of interest include, but are not limited to, Video Generation, World Models, 4D Reconstruction, Multi-Modal Models, Multi-View Geometry, Data Augmentation, and Video-Language-Action models, with a primary focus on foundation models for embodied applications. We are aiming to make progress on some of the hardest scientific challenges around spatio-temporal reasoning, and how it can lead to the deployment of autonomous agents in real-world unstructured environments. The Opportunity Our Learning From Videos (LFV) team is looking for a Computer Vision Research Scientist with expertise in Video Generation, Spatio-temporal Representation Learning, World Models, Foundation Models, Multi-Modal Learning, Vision-as-Inverse-Graphics (including Differentiable Rendering), or related fields, to improve dynamic scene understanding for robots. We are working on some of the hardest scientific challenges around the safe and effective usage of large robotic fleets, simulation, and prior knowledge (geometry, physics, domain knowledge, behavioral science), not only for automation but also for human augmentation. As a Research Scientist, you will work with a team proposing, conducting, and transferring innovative research. You will use large amounts of sensory data (real and synthetic) to address open problems, train models at scale, publish at top academic venues, and test your ideas in the real world (including on our robots). You will also work closely with other teams at TRI to transfer and ship our most successful algorithms and models towards world-scale long-term autonomy and advanced assistance systems.Responsibilities Conduct high-reaching research that solves problems of high value and validates them in well established benchmarks and systems. Push the boundaries of knowledge and the state of the art in ML areas, including simulation, perception, prediction, and planning for autonomous driving and robotics. Partner with a multidisciplinary team including other research scientists and engineers across the CV team, TRI, Toyota, and our university partners. Present results in verbal and written communications, internally, at top international venues, and via open-source contributions to the community. Work closely with robotics and machine learning researchers and engineers to understand theoretical and practical needs. Lead collaborations with our external research partners and mentor research interns. Follow best practices producing maintainable code, both for internal use as well as for open-sourcing to the scientific community. Qualifications PhD or equivalent years of experience in Machine Learning, Robotics, Computer Vision, or a related field. Deep expertise in at least one key ML area among Computer Vision, Large-Scale Pre-Training, Multi-Modal Learning, World Models, 4D Reconstruction Consistent record of publishing at high-impact conferences/journals (CVPR, ICLR, NeurIPS, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.) on the aforementioned topics. Proficient at scientific Python, Unix, and a common DL framework (preferably PyTorch). Experience with distributed learning (especially on AWS) for large-scale training of foundation models is a plus. You can identify, propose, and lead new research efforts, working in collaboration with other researchers and engineers to complete it from initial idea to working solution. You are intrigued by large-scale challenges in ML, especially in the space of Robotics, Automated Driving, and for societal good in general. You are a reliable teammate. You like to think big and go deeper. You care about openness and delivering with integrity. Please submit a brief cover letter and add a link to Google Scholar to include a full list of publications when submitting your CV for this position. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The MissionWe are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, we're building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also utilizing high-quality simulation to augment real-world robot data with procedurally generated synthetic demonstrations. The TeamThe Robotics Machine Learning Team's charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in unstructured environments such as homes or factories. The JobWe have several research thrusts under our broad mission, and we are looking for a research scientist in any of these areas: -Data-efficient and general algorithms for learning robust policies using multiple sensing modalities: proprioception, images, 3D representations, force, and dense tactile sensing.-Scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video.-Leveraging test time computation for embodied applications.-Quick and efficient improvement of learned policies.-Continual Learning and Adaption-Multi-Modal Reasoning Models.-Structured hierarchical reasoning using learned models.-Reinforcement Learning with Language Action Models -Leveraging history and memory for learning policies for long context tasks.-Improving robustness and few-shot generalization by using sub-optimal and self-play data. -Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification. The researcher who joins will be encouraged to collaborate in our code infrastructure, work together with team members, run experiments with both simulated and real (physical) robots, and participate in publishing work to peer-reviewed venues and open-sourcing code. We're looking for a research scientist who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data. Qualifications Hands-on experience with using machine learning for learned control, including RL, offline RL or behavior cloning, for manipulation. Or experience with machine learning and familiarity with large multi-modal datasets and models. Strong software development skills in Python. A “make it happen” demeanour and comfort with fast prototyping. A passion for robotics and doing research grounded in important fundamental problems. A track record of relevant publications in top international conferences (RSS, NeuRIPS, ICML, ICLR, CoRL, ICRA, IROS, …) Bonus Qualifications Hardware experience A track record of relevant open-source software contributions Experience working with large-scale datasets and multi-node training The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The Mission We are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, we're building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also utilizing high-quality simulation to augment real-world robot data with procedurally generated synthetic demonstrations. The Team The Robotics Machine Learning Team's charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in unstructured environments such as homes or factories. The Job We have several research thrusts under our broad mission, and we are looking for a research scientist in any of these areas: * Data-efficient and general algorithms for learning robust policies using multiple sensing modalities: proprioception, images, 3D representations, force, and dense tactile sensing. * Scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video. * Leveraging test time computation for embodied applications. * Quick and efficient improvement of learned policies. * Continual Learning and Adaption * Multi-Modal Reasoning Models. * Structured hierarchical reasoning using learned models. * Reinforcement Learning with Language Action Models * Leveraging history and memory for learning policies for long context tasks. * Improving robustness and few-shot generalization by using sub-optimal and self-play data. * Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification. The researcher who joins will be encouraged to collaborate in our code infrastructure, work together with team members, run experiments with both simulated and real (physical) robots, and participate in publishing work to peer-reviewed venues and open-sourcing code. We're looking for a research scientist who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data. Qualifications * Hands-on experience with using machine learning for learned control, including RL, offline RL or behavior cloning, for manipulation. Or experience with machine learning and familiarity with large multi-modal datasets and models. * Strong software development skills in Python. * A "make it happen" demeanour and comfort with fast prototyping. * A passion for robotics and doing research grounded in important fundamental problems. * A track record of relevant publications in top international conferences (RSS, NeuRIPS, ICML, ICLR, CoRL, ICRA, IROS, …) Bonus Qualifications * Hardware experience * A track record of relevant open-source software contributions * Experience working with large-scale datasets and multi-node training The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAt Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. Within the Human Interactive Driving division, the Extreme Performance Intelligent Control department is working to develop scalable, human-like driving intelligence by learning from expert human drivers. This project focuses on creating a configurable, data-driven world model that serves as a foundation for intelligent, multi-agent reasoning in dynamic driving environments. By tightly integrating advances in perception, world modeling, and model-based reinforcement learning, we aim to overcome the limitations of more compartmentalized, rule-based approaches. The end goal is to enable robust, adaptable, and interpretable driving policies that generalize across tasks, sensor modalities, and public road scenarios-delivering ground-breaking improvements for ADAS, autonomous systems, and simulation-driven software development. We are seeking a forward-thinking Research Scientist to focus on inferring latent state representations from sensor data, powering world models, and supporting rigorous policy evaluation for autonomous vehicles. This role spans raw perception and structured representations, enabling both high-fidelity predictive modeling and reliable policy assessment in simulated or learned environments. You will work closely with researchers developing world models and those focused on policy evaluation, ensuring that the latent states inferred from real-world sensors are semantically rich, temporally coherent, and suitable for both long-horizon prediction and counterfactual analysis.Responsibilities Design and train learning-based systems that transform raw multimodal sensor data (e.g., images, lidar, radar) into compact, dynamic latent states suitable for use in learned world models. Investigate unsupervised, self-supervised, and contrastive methods to learn latent spaces that encode dynamics, semantics, and uncertainty. Incorporate temporal information and motion consistency into latent state estimation using recurrent, filtering, or transformer-based architectures. Combine data from heterogeneous modalities into a unified latent state representations that generalize across conditions and scenarios. Ensure the learned representations are resilient to occlusion, sensor degradation, and distributional shift. Collaborate on joint research agendas with world modeling and policy evaluation researchers to explore uncertainty modeling, interpretability, and representation bottlenecks. Publish novel research, contribute to open-source tools, and engage with the academic community at major ML and robotics conferences. Qualifications PhD in Computer Science, Machine Learning, Robotics, or a related field. Strong foundation in representation learning or state estimation for sequential decision-making. Robust experience in deep generative models (e.g., VAEs, diffusion models, autoregressive models). Solid base in perception models from large-scale real-world sensor datasets from autonomous driving, robotics, or similar domains. Experience with latent world models, generative AI for perception, or contrastive learning. Familiarity with structure-from-motion, Gaussian splatting, or neural radiance fields (NeRFs). Experience with multi-modal sensor fusion, state estimation, and SLAM techniques. Familiarity with uncertainty-aware perception, active perception, and predictive modeling. Accomplished publication record at top-tier conferences such as NeurIPS, CVPR, ICCV, ICLR, ICRA, CoRL, or RSS. Deep programming skills in Python and deep learning frameworks such as PyTorch or JAX. Excellent problem-solving skills and the ability to work in a fast-paced team research environment. Bonus Qualifications Background building or using world models in model-based RL, planning, or simulation. Familiarity with latent-space rollouts, policy evaluation metrics, or offline RL tools. Knowledge working in high-dimensional, real-time environments with latency constraints. Please add a link to Google Scholar to include a full list of publications when submitting your CV for this position. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAt Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The MissionWe are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, we're building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also utilizing high-quality simulation to augment real-world robot data with procedurally generated synthetic demonstrations. The TeamThe Robotics Machine Learning Team's charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in unstructured environments such as homes or factories. The JobWe have several research thrusts under our broad mission, and we are looking for a research scientist in any of these areas: -Data-efficient and general algorithms for learning robust policies using multiple sensing modalities: proprioception, images, 3D representations, force, and dense tactile sensing.-Scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video.-Leveraging test time computation for embodied applications.-Quick and efficient improvement of learned policies.-Continual Learning and Adaption-Multi-Modal Reasoning Models.-Structured hierarchical reasoning using learned models.-Reinforcement Learning with Language Action Models -Leveraging history and memory for learning policies for long context tasks.-Improving robustness and few-shot generalization by using sub-optimal and self-play data. -Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification. The researcher who joins will be encouraged to collaborate in our code infrastructure, work together with team members, run experiments with both simulated and real (physical) robots, and participate in publishing work to peer-reviewed venues and open-sourcing code. We're looking for a research scientist who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data. Qualifications Hands-on experience with using machine learning for learned control, including RL, offline RL or behavior cloning, for manipulation. Or experience with machine learning and familiarity with large multi-modal datasets and models. Strong software development skills in Python. A “make it happen” demeanour and comfort with fast prototyping. A passion for robotics and doing research grounded in important fundamental problems. A track record of relevant publications in top international conferences (RSS, NeuRIPS, ICML, ICLR, CoRL, ICRA, IROS, …) Bonus Qualifications Hardware experience A track record of relevant open-source software contributions Experience working with large-scale datasets and multi-node training The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAt Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The Mission Make general-purpose robots a reality. The Challenge We envision a future where robots assist with household chores and cooking, aid the elderly in maintaining their independence, and enable people to spend more time on the activities they enjoy most. To achieve this, robots must be able to operate reliably in complex, unstructured environments. Our mission is to answer the question “What will it take to create truly general-purpose robots that can accomplish a wide variety of tasks in settings like human homes with minimal human supervision?” We believe that the answer lies in cultivating large-scale datasets of physical interaction from a variety of sources and building on the latest advances in machine learning to learn general purpose robot behaviors from this data. The Team The Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc.) data from multiple domains (driving, robotics, indoors, outdoors, etc.) to improve the performance of downstream tasks. This paradigm targets training scalability, since data from multiple modalities can be equally leveraged to learn useful data-driven priors (3D geometry, physics, dynamics, etc) for world understanding. Our topics of interest include, but are not limited to, Video Generation, World Models, 4D Reconstruction, Multi-Modal Models, Multi-View Geometry, Data Augmentation, and Video-Language-Action models, with a primary focus on foundation models for embodied applications. We are aiming to make progress on some of the hardest scientific challenges around spatio-temporal reasoning, and how it can lead to the deployment of autonomous agents in real-world unstructured environments. The Opportunity Our Learning From Videos (LFV) team is looking for a Computer Vision Research Scientist with expertise in Video Generation, Spatio-temporal Representation Learning, World Models, Foundation Models, Multi-Modal Learning, Vision-as-Inverse-Graphics (including Differentiable Rendering), or related fields, to improve dynamic scene understanding for robots. We are working on some of the hardest scientific challenges around the safe and effective usage of large robotic fleets, simulation, and prior knowledge (geometry, physics, domain knowledge, behavioral science), not only for automation but also for human augmentation. As a Research Scientist, you will work with a team proposing, conducting, and transferring innovative research. You will use large amounts of sensory data (real and synthetic) to address open problems, train models at scale, publish at top academic venues, and test your ideas in the real world (including on our robots). You will also work closely with other teams at TRI to transfer and ship our most successful algorithms and models towards world-scale long-term autonomy and advanced assistance systems.Responsibilities Conduct high-reaching research that solves problems of high value and validates them in well established benchmarks and systems. Push the boundaries of knowledge and the state of the art in ML areas, including simulation, perception, prediction, and planning for autonomous driving and robotics. Partner with a multidisciplinary team including other research scientists and engineers across the CV team, TRI, Toyota, and our university partners. Present results in verbal and written communications, internally, at top international venues, and via open-source contributions to the community. Work closely with robotics and machine learning researchers and engineers to understand theoretical and practical needs. Lead collaborations with our external research partners and mentor research interns. Follow best practices producing maintainable code, both for internal use as well as for open-sourcing to the scientific community. Qualifications PhD or equivalent years of experience in Machine Learning, Robotics, Computer Vision, or a related field. Deep expertise in at least one key ML area among Computer Vision, Large-Scale Pre-Training, Multi-Modal Learning, World Models, 4D Reconstruction Consistent record of publishing at high-impact conferences/journals (CVPR, ICLR, NeurIPS, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.) on the aforementioned topics. Proficient at scientific Python, Unix, and a common DL framework (preferably PyTorch). Experience with distributed learning (especially on AWS) for large-scale training of foundation models is a plus. You can identify, propose, and lead new research efforts, working in collaboration with other researchers and engineers to complete it from initial idea to working solution. You are intrigued by large-scale challenges in ML, especially in the space of Robotics, Automated Driving, and for societal good in general. You are a reliable teammate. You like to think big and go deeper. You care about openness and delivering with integrity. Please submit a brief cover letter and add a link to Google Scholar to include a full list of publications when submitting your CV for this position. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAt Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. Within the Human Interactive Driving division, the Extreme Performance Intelligent Control department is working to develop scalable, human-like driving intelligence by learning from expert human drivers. This project focuses on creating a configurable, data-driven world model that serves as a foundation for intelligent, multi-agent reasoning in dynamic driving environments. By tightly integrating advances in perception, world modeling, and model-based reinforcement learning, we aim to overcome the limitations of more compartmentalized, rule-based approaches. The end goal is to enable robust and adaptable, driving policies that generalize across tasks, sensor modalities, and public road scenarios-delivering ground-breaking improvements for ADAS, autonomous systems, and simulation-driven software development. We are seeking a highly motivated Research Scientist specializing in uncertainty-aware world models for autonomous vehicles. In this role, you will develop cutting-edge models that enable autonomous systems to perceive, predict, and interact intelligently with their environment. You will work at the intersection of machine learning, computer vision, robotics, and probabilistic modeling to build robust world models that improve perception, planning, and decision-making in self-driving systems.Responsibilities Develop and refine world models that improve the understanding of sophisticated and dynamic driving environments. Research and implement deep learning, reinforcement learning, and probabilistic modeling techniques for improved scene representation and prediction. Design algorithms that integrate sensor fusion, temporal reasoning, and uncertainty estimation to improve autonomous vehicle behavior. Collaborate with cross-functional teams, including perception, planning, and simulation engineers, to develop real-time, scalable models for deployment. Conduct experiments, simulations, and real-world validations to assess the effectiveness of world models. Publish research findings in premier conferences and journals and contribute to the AI and robotics research community. Stay up to date with advancements in machine learning, generative modeling, and simulation technologies. Qualifications Ph.D. (or equivalent experience) in Machine Learning, Computer Science, Robotics, or a related field. Strong background in probabilistic modeling, reinforcement learning, and deep learning architectures (e.g., Transformers, VAEs, Diffusion Models). Strong understanding of Bayesian inference, state-space models, and uncertainty quantification. Hands-on experience with world models, predictive modeling, or generative modeling in robotics or autonomous systems. Prior experience in publishing research at NeurIPS, ICML, CVPR, ICRA, or similar. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, JAX). Experience working with autonomous vehicle datasets, sensor modalities (LiDAR, camera, radar), and simulation environments. Excellent problem-solving skills and the ability to work in a fast-paced team research environment. Please submit a brief cover letter and add a link to Google Scholar to include a full list of publications when submitting your CV for this position. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job DescriptionAt Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The MissionTo conduct cutting-edge research that will enable general-purpose robots to be reliably deployed at scale in human environments. The ChallengeWe envision a future where robots assist with household chores and cooking, aid the elderly in maintaining their independence, and enable people to spend more time on the activities they enjoy most. To achieve this, robots need to be able to operate reliably in messy, unstructured environments. Recent years have witnessed a surge in the use of foundation models in various application domains, particularly in robotics. These “large behavior models” (LBMs) are enhancing the abilities of autonomous robots to perform various complex tasks in open and interactive environments. TRI Robotics is at the forefront of this emerging field by applying insights from foundation models, including large-scale pre-training and generative deep learning. However, it remains a challenge to ensure the reliability of LBMs for large-scale deployment in diverse operating conditions. The TeamWe aim to make progress on some of the hardest scientific challenges around the safe and effective usage and development of machine learning algorithms within robotics. To this end, the research mission of the Trustworthy Learning under Uncertainty (TLU) team within the Robotics division is to enable the robust, reliable, and adaptive deployment of LBMs at scale in human environments. To guarantee dependable deployment at scale in the years to come, we are dedicated to enhancing trustworthiness of LBMs through three key principles, as detailed (i) ensuring objective assessment of policy performance (Rigorous Evaluation), (ii) improving the ability to detect and handle unknown situations and return to nominal performance (Failure Detection and Mitigation), and (iii) developing the capability to identify and adapt to new information (Active / Continual Learning). Our team has deep cross-functional expertise across controls, uncertainty-aware ML, statistics, and robotics. We measure our success in terms of algorithmic advancements in the state-of-the-art and publications of these results in high-impact journals and conferences. We value contributions of reproducible and usable open-source software. The OpportunityWe're looking for a driven research scientist or research engineer with a strong background in embodied machine learning and a “make it happen” mentality. Specifically, we are looking for expertise in a variety of areas such as Policy Evaluation, Failure Detection and Mitigation, and Active Learning in the context of Large Behavior Models (LBMs) for robotic manipulation. Our topics of interest include but are not limited to: Multi-Modal Foundation Models, Generative Modeling, Imitation Learning, Reinforcement Learning, Planning & Control, Statistics, Uncertainty Estimation, Out-of-Distribution Detection, Safety-Aware & Robust ML, (Inter) Active Learning, and Online / Continual Learning. The ideal candidate is able to conduct research independently, but also works well as part of a larger research team at the cutting edge of state-of-the-art robotics and machine learning. Experience with robots is preferred, particularly in the manipulation domain. If our mission of robust, reliable, and adaptive deployment of LBMs at scale in human environments resonates with you, reach out by submitting an application!Responsibilities Work as part of a dynamic, closely-knit team conducting research on reliable, robust, and adaptive deployment of machine learning models in robot manipulation. Push the boundaries of knowledge and the state-of-the-art in Robotics and LBMs. Contribute to cutting-edge development in the areas of: Rigorous Policy Evaluation, Failure Detection and Mitigation, and Active / Continual Learning. Be a key member of the team and play a critical role in rapid progress measured by both the development of internal capabilities and high-impact external publication. Collaborate with internal research scientists and engineers across the TLU team, Robotics division, TRI, and Toyota, as well as our university partners across top academic research universities, such as MIT, Stanford, CMU, Columbia, USC, and Princeton. Present results in verbal and written communications at international conferences, internally, and via open-source contributions to the community. Qualifications 4+ years of relevant industry experience or a Ph.D. in Machine Learning, Robotics, or related fields. Passionate about large scale challenges in ML grounded in physical systems, especially in the space of robotic manipulation. Expertise in Multi-Modal Foundation Models, Generative Modeling, Imitation Learning, Reinforcement Learning, Planning & Control, Statistics, Uncertainty Estimation, Out-of-Distribution Detection, Safety-Aware & Robust ML, (Inter) Active Learning, and/or Online / Continual Learning. A strong track record of publication at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, ICML, UAI, AISTATS, AAAI, TMLR, RSS, ICRA, IROS, RA-L, T-RO, CDC, L4DC, etc.) on some of the aforementioned topics. Proficiency with one or more coding languages and systems, preferably Python, Unix, and a Deep Learning framework (e.g., PyTorch). Ability to collaborate with other researchers and engineers of the TLU team, and, more broadly, the Robotics division to invent and develop interesting research ideas. A reliable teammate who loves to think big, go deeper, and deliver with integrity. Bonus Qualifications Some familiarity with robots and the challenges inherent in conducting research on physical hardware platform. Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management is also useful. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The Team TRI's Carbon Neutrality Department within our Human-Centered AI (HCAI) Division blends behavioral science, human-computer interaction research, and machine learning to understand, predict and enable carbon neutral behavior. The Opportunity We are looking for a research scientist who has expertise in and enthusiasm for building AI-backed applications that push the boundaries of human-centered science. This work will involve working closely with experts in AI and behavior science to integrate machine learning models into live applications. The researcher should be comfortable iterating prototypes rapidly as they build toward the design and development of robust systems. The researcher should have a broad range of interests spanning social science, psychology, generative AI, user experience, HCI, and design. The researcher should be able to leverage systems they build to support research projects in all of these domains and lead a research project in at least one of them.Responsibilities Collaborate cross-functionally with specialists in multiple fields, as well as university partners, to research and develop technology that incorporates AI models into the design of interactive systems. Develop real-time, full-stack, interactive prototypes across a range of modalities, including in-vehicle, web, and mobile. Conduct basic user experience studies (e.g., heuristic evaluations, cognitive walkthroughs, Wizard of Oz, etc.) on their own. Work with experts in human behavior to conduct more thorough evaluations of prototypes. Adjust prototypes to support research goals and integrate extensive logging features. Work with an engineering team to build out robust, scalable versions of their prototypes. Support the research goals of others on the team while also advancing their own research agenda. Stay up to date on the state-of-the-art in AI models, APIs, integration frameworks, and scalable AI model deployment solutions. Collaborate with scientists in the Carbon Neutrality Department to shape our research program and to communicate research to Toyota partners. Publish findings in academic journals and/or conferences. Contribute to the technology transfer of research throughout Toyota. Qualifications PhD in Computer Science, HCI/Human Centered Design, Information/Information Management and Systems, or related multidisciplinary fields. 3+ years of experience prototyping and deploying applied AI projects. Full-stack web programming proficiency (preference for Python or similar on the backend and JS and JS frameworks and libraries on the frontend, but full-stack libraries such as Next.js/Node/React, Django, Flask, FastAPI, Laravel, etc., or also acceptable). Familiarity with at least one AI framework (such as PyTorch, TensorFlow, Hugging Face, or similar). Familiarity with at least one method of mobile prototyping (such as mobile web, iOS, or Android, or a cross-platform framework such as React Native, Flutter, or similar). Experience with at least one framework supporting AI model hosting and deployment to live applications (such as AWS Sagemaker/Lambda, Google Cloud Vertex AI, or Azure ML, or similar). Familiarity with data storage techniques (such as NoSQL/MongoDB, and/or DynamoDB, MySQL, PostgreSQL, or similar). Willingness to learn new frameworks. Some experience in human-centered research (e.g. behavioral data science, computational social science, human-computer interaction), including qualitative and/or quantitative methods such as experiments and user studies. Broad knowledge of applied machine learning approaches. Ability to work collaboratively across subject areas and functions. Strong project management skills and a desire to work on challenging, open-ended research projects. Demonstrated ability to work autonomously while soliciting feedback. Strong interpersonal skills and a great teammate. High interest in research to facilitate carbon neutrality. Ability to communicate complex concepts clearly across different audiences. Bonus Qualifications Familiarity with data science toolkits (e.g., Python Pandas, NumPy, etc.). Knowledge of methods to support asynchronous requests (such as Celery, Redis, RabbitMQ, Amazon SQS, or similar). Experience with fine-tuning approaches (e.g., LoRA). Ability to balance multiple projects, including short-term, targeted analyses and novel, innovative projects that may span several years. The pay range for this position at commencement of employment is expected to be between $152,000 and $228,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

Job DescriptionAt Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The Team TRI's Carbon Neutrality Department within our Human-Centered AI (HCAI) Division blends behavioral science, human-computer interaction research, and machine learning to understand, predict and enable carbon neutral behavior. The Opportunity We are looking for a research scientist who has expertise in and enthusiasm for building AI-backed applications that push the boundaries of human-centered science. This work will involve working closely with experts in AI and behavior science to integrate machine learning models into live applications. The researcher should be comfortable iterating prototypes rapidly as they build toward the design and development of robust systems. The researcher should have a broad range of interests spanning social science, psychology, generative AI, user experience, HCI, and design. The researcher should be able to leverage systems they build to support research projects in all of these domains and lead a research project in at least one of them.Responsibilities Collaborate cross-functionally with specialists in multiple fields, as well as university partners, to research and develop technology that incorporates AI models into the design of interactive systems. Develop real-time, full-stack, interactive prototypes across a range of modalities, including in-vehicle, web, and mobile. Conduct basic user experience studies (e.g., heuristic evaluations, cognitive walkthroughs, Wizard of Oz, etc.) on their own. Work with experts in human behavior to conduct more thorough evaluations of prototypes. Adjust prototypes to support research goals and integrate extensive logging features. Work with an engineering team to build out robust, scalable versions of their prototypes. Support the research goals of others on the team while also advancing their own research agenda. Stay up to date on the state-of-the-art in AI models, APIs, integration frameworks, and scalable AI model deployment solutions. Collaborate with scientists in the Carbon Neutrality Department to shape our research program and to communicate research to Toyota partners. Publish findings in academic journals and/or conferences. Contribute to the technology transfer of research throughout Toyota. Qualifications PhD in Computer Science, HCI/Human Centered Design, Information/Information Management and Systems, or related multidisciplinary fields. 3+ years of experience prototyping and deploying applied AI projects. Full-stack web programming proficiency (preference for Python or similar on the backend and JS and JS frameworks and libraries on the frontend, but full-stack libraries such as Next.js/Node/React, Django, Flask, FastAPI, Laravel, etc., or also acceptable). Familiarity with at least one AI framework (such as PyTorch, TensorFlow, Hugging Face, or similar). Familiarity with at least one method of mobile prototyping (such as mobile web, iOS, or Android, or a cross-platform framework such as React Native, Flutter, or similar). Experience with at least one framework supporting AI model hosting and deployment to live applications (such as AWS Sagemaker/Lambda, Google Cloud Vertex AI, or Azure ML, or similar). Familiarity with data storage techniques (such as NoSQL/MongoDB, and/or DynamoDB, MySQL, PostgreSQL, or similar). Willingness to learn new frameworks. Some experience in human-centered research (e.g. behavioral data science, computational social science, human-computer interaction), including qualitative and/or quantitative methods such as experiments and user studies. Broad knowledge of applied machine learning approaches. Ability to work collaboratively across subject areas and functions. Strong project management skills and a desire to work on challenging, open-ended research projects. Demonstrated ability to work autonomously while soliciting feedback. Strong interpersonal skills and a great teammate. High interest in research to facilitate carbon neutrality. Ability to communicate complex concepts clearly across different audiences. Bonus Qualifications Familiarity with data science toolkits (e.g., Python Pandas, NumPy, etc.). Knowledge of methods to support asynchronous requests (such as Celery, Redis, RabbitMQ, Amazon SQS, or similar). Experience with fine-tuning approaches (e.g., LoRA). Ability to balance multiple projects, including short-term, targeted analyses and novel, innovative projects that may span several years. The pay range for this position at commencement of employment is expected to be between $152,000 and $228,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. This internship opportunity is a paid 12-week internship for Summer 2026. Please note that this internship will be a hybrid in-office role. The Mission Our team uses design thinking process to place the human at the center of determining the needs, design, and implementation of human-machine interfaces. By following this process, the HMIR team creates automotive HMI technologies that allow humans of any ability to work in harmony with AI. The Team In the Human-Machine Interaction Research group (HMIR), we design, develop and evaluate novel interfaces to improve the safety, well-being, and performance of drivers using human-centered artificial intelligence. The Internship As a Research Intern, you will work on a project focused on improving driving safety and performance using the driver's behavioral, cognitive, and emotional states. There will be opportunities to design and run experiments in our driving motion simulator to study how different driver traits and states lead to unsafe driving behaviors, and how human-machine interfaces can be used to improve the driving experience. An ideal candidate should have experience running experiments with human subjects and should be pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields. Experience with machine learning, measuring physiological signals (e.g., EDA, heart rate), and eye-tracking is a plus. You will work with a strong team of researchers, and the expected outcome is to have a publication at a human-computer interaction or cognitive science journal/conference. Responsibilities * Conduct user studies to evaluate the effectiveness and responses to different interventions to improve driving safety and performance. * Create novel interventions that can be used to help people drive better and safer. * Partner with a multidisciplinary team including other research scientists and engineers across Toyota Research Institute. * Present results in verbal and written communications, both internally and at top international venues. Qualifications * Currently pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields. * Experience designing and running experiments with human subjects. * Past cross-functional collaboration with other researchers and engineers to invent and develop interesting research ideas. * You are passionate about developing and applying human-centered artificial intelligence for social good. * You are a reliable team player. You like to think big and go deeper. You care about openness and delivering with integrity. * Experience with machine learning is a plus. * Experience with devices to measure physiological signals is a plus (e.g., EDA, heart rate).Experience with eye-tracking devices is a plus. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles. Base pay offered may vary depending on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. This internship opportunity is a paid 12-week internship for Summer 2026. Please note that this internship will be a hybrid in-office role. The Mission Our team uses design thinking process to place the human at the center of determining the needs, design, and implementation of human-machine interfaces. By following this process, the HMIR team creates automotive HMI technologies that allow humans of any ability to work in harmony with AI. The Team In the Human-Machine Interaction Research group (HMIR), we design, develop and evaluate novel interfaces to improve the safety, well-being, and performance of drivers using human-centered artificial intelligence. The Internship As a Research Intern, you will work on a project focused on improving driving safety and performance using the driver's behavioral, cognitive, and emotional states. There will be opportunities to design and run experiments in our driving motion simulator to study how different driver traits and states lead to unsafe driving behaviors, and how human-machine interfaces can be used to improve the driving experience. An ideal candidate should have experience running experiments with human subjects and should be pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields. Experience with machine learning, measuring physiological signals (e.g., EDA, heart rate), and eye-tracking is a plus. You will work with a strong team of researchers, and the expected outcome is to have a publication at a human-computer interaction or cognitive science journal/conference.Responsibilities Conduct user studies to evaluate the effectiveness and responses to different interventions to improve driving safety and performance. Create novel interventions that can be used to help people drive better and safer. Partner with a multidisciplinary team including other research scientists and engineers across Toyota Research Institute. Present results in verbal and written communications, both internally and at top international venues. Qualifications Currently pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields. Experience designing and running experiments with human subjects. Past cross-functional collaboration with other researchers and engineers to invent and develop interesting research ideas. You are passionate about developing and applying human-centered artificial intelligence for social good. You are a reliable team player. You like to think big and go deeper. You care about openness and delivering with integrity. Experience with machine learning is a plus. Experience with devices to measure physiological signals is a plus (e.g., EDA, heart rate).Experience with eye-tracking devices is a plus. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles. Base pay offered may vary depending on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. This is a summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Internship As a Research Intern, you will work with a multidisciplinary team proposing, conducting, and transferring pioneering research on the intersection between Computer Vision and Robotics. You will use large amounts of data from different sources and modalities, and train large-scale foundation models aimed at solving open problems, work towards publications at top academic venues, and test your ideas in simulators as well as in the real world. The Team The Learning From Videos (LFV) team in the Robotics division is looking for research interns for the summer of 2026 in a variety of areas such as Video Generation, World Modeling, 4D Reconstruction, Multi-Modal Foundation Models, Multi-View Geometry, Data Augmentation, and Large Vision Models, with a primary focus on on embodied applications. We are aiming to make progress on some of the hardest scientific challenges around the deployment of robots in real-world unstructured environments, by leveraging data from different sources and modalities, and learning transferable priors grounded in the physical properties of the world. Our mission is to develop foundational models capable of understanding how the world works, and in doing so predict possible future states and adapt to new environments and circumstances. Responsibilities Conduct daring research in Computer Vision that solves open problems of high theoretical and practical value, and evaluate solutions on real-world benchmarks and systems, with a focus on robotics. Push the boundaries of knowledge and the state-of-the-art in Visual Systems for Robotics. Partner with a multidisciplinary team, including other research scientists and engineers across the LFV team, the Robotics division, TRI, Toyota, and our university partners. Stay up to date on the state-of-the-art in Machine Learning ideas and software. Present results in verbal and written communications at international conferences, internally, and via open-source contributions to the community. Qualifications Currently pursuing a Ph.D. in Machine Learning, Robotics, or related fields. Publication or desire to publish at high-impact conferences/journals (e.g., CoRL, ICLR, NeurIPS, CVPR, ICCV, ECCV, ICML, UAI, AISTATS, AAAI, TMLR, RSS, ICRA, IROS, RA-L, etc.) on some of the aforementioned topics. Passionate about large scale challenges in ML and CV grounded in physical systems, especially in the space of robotics. Proficiency with one or more coding languages and systems, preferably Python, Unix, and a Deep Learning framework (e.g., PyTorch). Ability to collaborate with other researchers and engineers of the LFV team, and, more broadly, the Robotics division to invent and develop interesting research ideas. A reliable teammate who loves to think big, go deeper, and deliver with integrity. Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. Our driving simulator is physically located there and the intern is expected to test and deploy software on the platform, as well as collaborate with other researchers. The Team The Human Interactive Driving (HID) Research group is focused on designing the future of advanced safety systems, pushing the envelope of safety, driver experience, and automation. Our team consists of cognitive scientists, computer scientists, software engineers, mechanical and electrical engineers, vehicle dynamics experts, designers, and more. We leverage multiple simulation and physical platforms to explore novel interfaces, algorithms, and safety technologies. Our group is developing next-generation training and assessment tools for performance driving and beyond. We are looking into expanding our driving simulation technology by generating novel driving courses, including layout and other features, based on individual drivers' skill levels, past performance, and long-horizon strategy development. These tracks may also be used to train autonomous and shared autonomy artificial agents The Internship We are looking for a 2026 summer research intern in our Los Altos HQ to work on this effort, with an aim of approaching this as a research challenge for combining generative AI and human-factors research. This intern will be expected to work hands-on with a physical simulation system, create working code prototypes, interact frequently with team members, transfer code, design validation experiments, and participate in writing a paper describing the findings, as well as publishing the work. Responsibilities Procedural track generation using generative AI, involving the design and implementation of new or extended generative methods to create novel driving environments. Dynamic content creation for our CARLA-based driving simulator, integrating AI-driven or algorithmic content into interactive simulation systems such as CARLA, Unreal, or similar platforms. Driver skill assessment, contributing to the development and validation of models that characterize driver behavior, measure performance, and support human-centered evaluation. Qualifications Currently at-least second year pursuing a Ph.D. in Computer Science, Robotics, Human-Robot Interaction, or related fields. Experience in generative AI, whether LLMs with non-language tokens or diffusion models. Game development experience: Unreal, Unity, Godot, etc. and/or simulation development experience: CARLA, Sumo, Gazebo, AirSim, etc. Strong software engineering skills (C++/Python preferred) and analysis/debugging robotic systems. Experience working in a shared codebase with multiple collaborators and reviewing others' code. Strong written and oral communication skills. Experience in working in multi-disciplinary teams. You will be working cross-functionally with UX/UI designers, human-factors researchers, and cognitive scientists. Must have a high level of self-initiative to prioritize and manage workload and meet project deadlines in a dynamic environment. Bonus Qualifications Prior experience in ROS / ROS2. Prior experience with human subjects or human-centric research. Prior experience in scientific Python, R, or similar statistical analysis tools. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles, and between $40 and $58/hour for Massachusetts-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. This internship opportunity is a paid 12-week internship for Summer 2026. Please note that this internship will be a hybrid in-office role. The Mission Our team uses design thinking process to place the human at the center of determining the needs, design, and implementation of human-machine interfaces. By following this process, the HMIR team creates automotive HMI technologies that allow humans of any ability to work in harmony with AI. The Team In the Human-Machine Interaction Research group (HMIR), we design, develop and evaluate novel interfaces to improve the safety, well-being, and performance of drivers using human-centered artificial intelligence. The Internship As a Research Intern, you will work on a project focused on improving driving safety and performance using the driver's behavioral, cognitive, and emotional states. There will be opportunities to design and run experiments in our driving motion simulator to study how different driver traits and states lead to unsafe driving behaviors, and how human-machine interfaces can be used to improve the driving experience. An ideal candidate should have experience running experiments with human subjects and should be pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields. Experience with machine learning, measuring physiological signals (e.g., EDA, heart rate), and eye-tracking is a plus. You will work with a strong team of researchers, and the expected outcome is to have a publication at a human-computer interaction or cognitive science journal/conference.Responsibilities Conduct user studies to evaluate the effectiveness and responses to different interventions to improve driving safety and performance. Create novel interventions that can be used to help people drive better and safer. Partner with a multidisciplinary team including other research scientists and engineers across Toyota Research Institute. Present results in verbal and written communications, both internally and at top international venues. Qualifications Currently pursuing a Ph.D. in Computer Science, Human-Computer Interaction, Cognitive Science, Psychology, Human Factors Engineering, or related fields. Experience designing and running experiments with human subjects. Past cross-functional collaboration with other researchers and engineers to invent and develop interesting research ideas. You are passionate about developing and applying human-centered artificial intelligence for social good. You are a reliable team player. You like to think big and go deeper. You care about openness and delivering with integrity. Experience with machine learning is a plus. Experience with devices to measure physiological signals is a plus (e.g., EDA, heart rate).Experience with eye-tracking devices is a plus. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles. Base pay offered may vary depending on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. Our driving simulator is physically located there and the intern is expected to test and deploy software on the platform, as well as collaborate with other researchers. The Team The Human Interactive Driving (HID) Research group is focused on designing the future of advanced safety systems, pushing the envelope of safety, driver experience, and automation. Our team consists of cognitive scientists, computer scientists, software engineers, mechanical and electrical engineers, vehicle dynamics experts, designers, and more. We leverage multiple simulation and physical platforms to explore novel interfaces, algorithms, and safety technologies. Our group is developing next-generation training and assessment tools for performance driving and beyond. We are looking into expanding our driving simulation technology by generating novel driving courses, including layout and other features, based on individual drivers' skill levels, past performance, and long-horizon strategy development. These tracks may also be used to train autonomous and shared autonomy artificial agents The Internship We are looking for a 2026 summer research intern in our Los Altos HQ to work on this effort, with an aim of approaching this as a research challenge for combining generative AI and human-factors research. This intern will be expected to work hands-on with a physical simulation system, create working code prototypes, interact frequently with team members, transfer code, design validation experiments, and participate in writing a paper describing the findings, as well as publishing the work. Responsibilities * Procedural track generation using generative AI, involving the design and implementation of new or extended generative methods to create novel driving environments. * Dynamic content creation for our CARLA-based driving simulator, integrating AI-driven or algorithmic content into interactive simulation systems such as CARLA, Unreal, or similar platforms. * Driver skill assessment, contributing to the development and validation of models that characterize driver behavior, measure performance, and support human-centered evaluation. Qualifications * Currently at-least second year pursuing a Ph.D. in Computer Science, Robotics, Human-Robot Interaction, or related fields. * Experience in generative AI, whether LLMs with non-language tokens or diffusion models. * Game development experience: Unreal, Unity, Godot, etc. and/or simulation development experience: CARLA, Sumo, Gazebo, AirSim, etc. * Strong software engineering skills (C++/Python preferred) and analysis/debugging robotic systems. * Experience working in a shared codebase with multiple collaborators and reviewing others' code. * Strong written and oral communication skills. * Experience in working in multi-disciplinary teams. You will be working cross-functionally with UX/UI designers, human-factors researchers, and cognitive scientists. * Must have a high level of self-initiative to prioritize and manage workload and meet project deadlines in a dynamic environment. Bonus Qualifications * Prior experience in ROS / ROS2. * Prior experience with human subjects or human-centric research. * Prior experience in scientific Python, R, or similar statistical analysis tools. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles, and between $40 and $58/hour for Massachusetts-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. We're developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we've built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences. The TeamThe Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc) data from multiple domains (driving, robotics, indoors, outdoors, etc) to improve the performance of downstream tasks. This paradigm targets training scalability, since data from multiple modalities can be equally leveraged to learn useful data-driven priors (3D geometry, physics, dynamics, etc) for world understanding. Our topics of interest include, but are not limited to, Video Generation, World Models, 4D Reconstruction, Multi-Modal Models, Multi-View Geometry, Data Augmentation, and Video-Language-Action models, with a primary focus on embodied applications. We are aiming to make progress on some of the hardest scientific challenges around spatio-temporal reasoning, and how it can lead to the deployment of autonomous agents in real-world unstructured environments. The PostdocThis year-long postdoctoral research position will be highly integrated into our team, with hands in both ongoing and new research and development threads in the areas of: 4D World ModelsPhysical and Embodied IntelligenceMulti-Modal Learning This researcher will have the opportunity to work collaboratively with our team at TRI on high-risk, high-reward projects, pushing forward our understanding of spatio-temporal reasoning and zero-shot generalization. This is a research-focused position, targeting the development of methods and techniques that can solve real-world problems. We welcome you to join a positive, friendly, and enthusiastic team of researchers, where you will contribute to helping people gain and maintain independence, access, and mobility. We work closely with other Toyota affiliates and actively collaborate towards research publications and the productization of our developed technologies.Responsibilities Develop, integrate, and deploy algorithms for Multi-Modal and 4D reasoning targeting physical applications. Handle the ingestion of large-scale datasets for training, including streaming, online, and continual learning. Invent and deploy innovative solutions at the intersection of machine learning, computer vision, and robotics that improve the real-world performance of useful tasks. Work closely with robotics and machine learning researchers and engineers to understand theoretical and practical needs. Follow best practices producing maintainable code, both for internal use as well as for open-sourcing to the scientific community. Qualifications Ph.D. in a relevant technical field. A strong background in computer vision and its applications to robotics and embodied systems. A standout colleague with strong communication skills, and an ability to learn from others and contribute back to the scientific community with publications or open source code. Passionate about assisting and amplifying older adults and those in need through dexterous manipulation, human-robot collaboration, and physical assistance innovation. Bonus Qualifications Spatio-temporal (4D) computer vision, including multi-view geometry, 3D/4D reconstruction, video generation, self-supervised learning, occlusion reasoning, etc. Large-scale training of multi-modal deep learning methods, both in terms of dataset sizes and model complexity, context length extension, and efficient attention, distributed computing, etc. Application of machine learning and computer vision to embodied applications. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant's race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.