Toyota Research Institute 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. This is a summer 2026 paid 12-week internship opportunity. Please note that this internship will be an in-office role. The Internship This internship will be embedded within the Robotics User Experience team, with the mission to design intuitive physical and digital experiences for managing and interacting with robots in a factory context. This internship will be an opportunity to explore applying the principles of user experience design in some of the following areas:Digital interfaces for managing a fleet of mobile robots within a factory setting. Tools for assisting factory team members in assuring the quality of manufactured parts. Physical and digital methods for interacting with robots (and for robots to interact with humans).Extending a platform for prototyping and testing robotics UX concepts. The Team The Robotics UX team is made up of UX designers, researchers, and engineers, and is based in TRI's Los Altos, CA office. We research and design robot interfaces for the manufacturing environment, and contribute directly to the design of robot prototypes for both research and applied projects. Qualifications Recent grad or pursuing a Bachelor's or Master's degree in HCI, Interaction Design, or a related field. A portfolio that demonstrates the user-centered design process and includes prototypes of varying fidelity. Able to work independently with some guidance from senior design staff; demonstrates a good understanding of best practices in design methodologies and tools. A keen eye for visual design and the ability to produce pixel-perfect design specifications. Experience in Figma, with a solid understanding of industry standards and features. Able to design a variety of UX artifacts, including personas, user journeys, prototypes, presentations, and UI mock-ups. Hands-on experience with a design system, and a strong grasp of best practices to ensure consistency within the team and across projects. Comfortable in a collaborative, interdisciplinary team environment with excellent visual, verbal, and written communication skills; comfortable receiving and incorporating constructive feedback. Bonus Qualifications Experience designing interfaces & interactions for a physical device, such as a robot. Experience using Raspberry Pi, Arduino, or other microcontrollers for prototyping interactions. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Team You'll be joining a multidisciplinary research team focused on developing a world foundation model for driving-a unified, transferable representation of driving knowledge built from large-scale real-world and simulated data. Together, we are tackling the complex challenges of multi-agent interaction, causal reasoning, and embodied intelligence in highly dynamic, real-world driving environments. Our approach is inspired by cutting-edge generative modeling techniques and powered by scalable infrastructure and open-source data, and we work closely with engineers to deploy our models in simulation and on hardware. The Internship As a Ph.D. Research Intern, you will conduct original research at the intersection of machine learning and autonomous driving. Your work may focus on developing novel components of world models, improving decision-making through model-based RL, advancing 3D perception for dynamic scenes, or enhancing simulation-to-reality transfer. You'll have the opportunity to prototype and evaluate your ideas in closed-loop simulations and contribute to research publications alongside TRI scientists. This is an opportunity to test and refine your research in a collaborative, high-impact environment, while working with real-world data and contributing to the future of autonomous systems. The internship will be in our headquarters and include competitive compensation, befitting the challenging but fun nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply.Responsibilities Conduct original research in one or more areas: world modeling, multi-agent interaction, reinforcement learning, perception, or simulation-to-reality transfer. Collaborate closely with full-time researchers on the design, training, and evaluation of learning-based driving systems. Contribute to building and experimenting with task-aware, multi-modal, and uncertainty-aware models. Develop and evaluate prototypes in closed-loop simulation environments and, time permitting, on high-performance autonomous driving hardware. Present research findings through internal talks and work towards a top-tier academic publication. Integrate and work with large-scale datasets (open-source and internal). Qualifications Currently enrolled in a Ph.D. program in Computer Science, Robotics, Machine Learning, or a related field. Strong background in machine learning, particularly in areas such as deep learning, generative models, reinforcement learning, or probabilistic modeling. Demonstrated experience with one or more of the following: World models (e.g., latent dynamics, diffusion-based models), Model-based RL or decision-making, 3D perception or sensor fusion, and Large-scale simulation for robotics or autonomous systems. Prior publication(s) in top-tier conferences (NeurIPS, ICLR, ICML, CVPR, ICRA, CoRL, etc.) Proficiency with Python and PyTorch. Familiarity with AWS services (S3, EC2, and SageMaker) and open-source driving datasets (nu Scenes, Waymo, Argoverse, etc.) is a plus. Please include links to any relevant open-source contributions or technical project write-ups with your application. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. The MissionMake general-purpose robots a reality. The ChallengeWe envision a future where robots assist with household chores and cooking, aid the older population 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. 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. Robotics The mission of TRI Robotics is to invent and prove new robotic capabilities required to enable home robots to solve the challenges faced by an aging society. As part of that mission, we are developing a sophisticated suite of open source robotics software called Drake (*********************** for use in our internal robotics projects and the wider community of advanced robotics researchers. TeamWithin TRI Robotics, the Dynamics and Simulation team develops Drake tools to model and simulate mobile robot dynamics, object manipulation, and perception. We emphasize physical accuracy and robust, performant software permitting controller synthesis, learning, analysis, regression testing, and design in simulation that transfers importantly to the real world. Features include: - Physics-based, high-fidelity, high-performance software tools for simulation of robots and vehicles interacting with their environments.- Multibody dynamics, rigid and soft body computational mechanics.- A unique hybrid dynamic system abstraction and infrastructure (like Simulink blocks, but differentiable and symbolically analyzable).- Solvers for dynamic systems (numerical integration of DAEs, time stepping, event handling).- Computational geometry and contact response (emphasizing manipulation).- Validation of simulation accuracy and verification of software and numerical methods. This is open-source, modern C++ software, developed using rigorous standard methodologies, including extensive unit and validation tests, and collaborative pre-merge peer review. We encourage publication of novel work in peer-reviewed literature and collaboration with the wider robotics community. We are looking for someone to help us move this software forward. The right candidate loves to program and enjoys the intricacies of crafting correct, appealing, and performant advanced C++ code as part of a similarly-devoted team. The team consists of computer scientists and engineers trained at leading academic institutions and innovative companies, with research and practical experience in robotics, computer graphics, computational geometry and mechanics, multibody dynamics, numerical methods, and software engineering. We have considerable expertise in all these fields and a lot of software to write, so there is much interesting work to do and plenty of opportunity to extend your knowledge in any of the above areas. There are many open problems to solve and the ideal candidate will contribute both quality code and novel solutions.Responsibilities Design and implement high-performance simulation tools for deformable body dynamics as part of our open-source robotics software stack. Collaborate with dynamics and simulation researchers to translate physical modeling needs into robust, scalable, and maintainable simulation code. Extend our open-source robotics toolkit, Drake, with new functionality for multiphysics simulation. Analyze and optimize performance bottlenecks in simulation pipelines to support real-time operation and large-scale batch processing. Develop automated test suites and validation pipelines to ensure correctness and physical fidelity of simulation results. Stay informed with the latest advances in numerical methods, parallel computing, and GPU architectures, and incorporate them into our tools. Contribute to technical publications and open-source collaborations as appropriate. Qualifications Strong programming skills in modern C++ and experience with GPU programming (CUDA, OpenCL, or similar). Solid foundation in numerical methods for physics-based deformable body simulation, including Finite Element Method (FEM), Material Point Method (MPM), or other approaches. Background in continuum mechanics, including stress-strain relationships, constitutive modeling, and large-deformation simulation. Experience implementing scientific or simulation software in a collaborative, production-quality codebase. Proficiency in linear algebra, differential equations, and numerical analysis. Strong communication skills and a collaborative approach. Bonus Qualifications Experience optimizing low-level code on modern GPU architectures (e.g., memory coalescing, shared memory usage, occupancy tuning). Familiarity with the Drake, Mujoco, or similar physics engines. Experience contributing to open-source scientific software and publishing research in simulation or graphics venues (e.g. SIGGRAPH, SIGGRAPH Asia, SCA, Eurographics). The pay range for this position at commencement of employment is expected to be between $180,000 and $270,000/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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. The Team The long-term vision of TRI's Accelerated Materials Design and Discovery (AMDD) program is to accelerate the development of truly emissions-free mobility. Realizing this vision will require the discovery of new materials and devices for batteries, fuel cells, and more. Our aim at TRI is to merge cutting-edge computational materials modeling, experimental data, artificial intelligence, and automation to significantly accelerate materials research. Our focus is on developing tools and capabilities to enable this acceleration. We collaborate closely with a dozen universities and national labs and colleagues across global Toyota. AMDD seeks to develop and translate the newest technologies into practice, both within Toyota and the open research community more broadly. The Internship We are looking for an intern to contribute to the development and/or benchmarking of our probabilistic programming tools. Together, we will develop tools that provide insight into the design and testing of fuel cells, electrolyzers, or related devices. Your day-to-day may include: probabilistic programming, time-series analysis, structural causal model development, and/or machine learning model development. We welcome you to join a unique team of scientists and engineers where you will constantly learn new skills at the interface of materials science and AI.Qualifications Currently enrolled in a doctoral program in computer science, statistics, applied math, machine learning, or a related discipline. Have experience with probabilistic programming or probabilistic machine learning applied to time series modeling. Have experience with standard machine learning tools in Python such as PyTorch, JAX, etc. Bonus: Have experience with structural causal modeling, causal inference, causal learning, and/or experience with chemistry or material science. 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 $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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. This is a summer 2026 paid 12-week internship opportunity. Please note that this internship will be an in-office role. The MissionWe are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, our team is building general-purpose machine learning foundation models for dexterous robot manipulation. These models 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 using high-quality simulation to augment real world robot data with procedurally-generated synthetic data. 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 InternshipWe have several research thrusts under our broad mission, and we are looking for a research intern in any of these areas: Data-efficient and general algorithms for learning robust policies leveraging multiple sensing modalities: proprioception, images, 3D representations, etc.Data annotation and filtering. Improving policies without collecting more data by using non-robotics data at scale, new training objectives, new data annotations, or filtered datasets.Scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video.Structured hierarchical reasoning using learned models Leveraging test time compute for embodied applications Multimodal reasoning models Reinforcement Learning for multimodal models Leveraging history and memory for learning policies for long context tasks.Improving robustness and few-shot generalization by leveraging sub-optimal and self-play data. Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification. The intern who joins our team will be expected to create working code prototypes, interact frequently with team members, run experiments with both simulated and real (physical) robots, and participate in publishing the work to peer-reviewed venues. We're looking for an intern who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data.Qualifications Experience with machine learning and familiarity with large multimodal datasets and models. OR Hands-on experience with using machine learning for learned control, including RL, offline RL or behavior cloning, for manipulation. Strong software development skills in Python. A “make it happen” attitude and comfort with fast prototyping. A passion for robotics and doing research grounded in important fundamental problems. Bonus Qualifications Hardware experience. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. The TeamWe're on a mission to improve the quality of human life by creating robots that can learn, adapt, and assist in everyday environments. We are building a world-class team to push the boundaries of robot learning, combining machine learning, perception, prediction, and action to produce robust and coordinated robot behaviors. The OpportunityWe're looking for a motivated Research Engineer to help develop the next generation of AI-powered robots through high-fidelity simulation and Large Behavior Models. In this role, you'll work at the intersection of machine learning, computer vision, robotics, and physics-based modeling to enable scalable and generalizable robot policy development. Experience with simulation or embodied systems (robots, autonomous vehicles, etc.) is a strong plus. As part of our team, you'll contribute to cutting-edge research while leveraging TRI's expertise in ML, cloud, software, and hardware to build systems that move from simulation to real-world deployment.Responsibilities Build, improve, and robustify end-to-end integrated ML pipelines for training multimodal (language, images, 3D, video, actions) models at scale. Develop and manage physics-based robot simulation environments enabling scalable training and evaluation of learning-based behavior models in realistic, physically grounded scenarios. Integrate and validate learned policies in simulation, assessing real-world applicability, generalization, and performance across diverse environments, tasks, geometries, and sensor viewpoints. Train, finetune, and serve robot foundation models with a strong MLOps mindset. Build processes for integrating collaboration-produced and open-source advancements and code into our internal stack. Collaborate with internal research scientists and our partner labs at top academic institutions and Toyota research labs to drive pioneering research at scale. Qualifications Bachelor's or master's degree in Computer Science, Robotics, Physics, or a related field. 2+ years of professional engineering experience at an AI/ML-focused organization. Strong proficiency in Python and experience with simulation frameworks such as Isaac Sim, PyBullet, MuJoCo, or similar. Hands-on experience with robotics simulation, reinforcement learning, or large-scale machine learning. Familiarity with state-of-the-art methods in behavior learning and/or computer vision. Experience integrating ML models into simulated or real-world environments. Extensive practical experience with PyTorch. Ability to alternate between rapid prototyping and production-quality implementation. Solid understanding of software engineering best practices, including testing, CI/CD, and documentation. Bonus Qualifications Experience deploying models on embodied systems/robots. Experience working in mixed teams of research scientists and engineers. Exposure to MLOps tools and infrastructure (e.g., Docker, EC2, S3, Sagemaker). 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 $128,000 and $192,000/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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Team The Automated Driving Advanced Development division at TRI will focus on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared commitment. This new division is leading a new cross-organizational project between TRI and Woven by Toyota to conduct research and develop a fully end-to-end learned driving stack. This cross-org collaborative project is harmonious with TRI's robotics divisions' efforts in Diffusion Policy and Large Behavior Models. The Internship We are looking for Machine Learning Research Interns to join our autonomy team and help bring end-to-end ML models ( pixels to trajectories ) into robust, testable, and deployable systems. This role is ideal for those who thrive at the intersection of machine learning, systems engineering, and real-world deployment. This internship opportunity is a paid 12-week internship for Summer 2026. Please note that this internship will be a hybrid in-office role. You'll contribute to the implementation, evaluation, and integration of ML-based components for perception, planning, and control; with simulation-based testing. You'll work closely with researchers, data engineers, and autonomy engineers to ensure models scale from prototype to production. This work is part of Toyota's global AI efforts to build a more coordinated global approach across Toyota entities. Responsibilities * Conduct ambitious research to advance the state-of-the-art in using new capabilities in generative modelling for end-to-end planning from vision in automated driving. * Implement scalable end-to-end architectures that process raw sensor data to generate vehicle trajectories, addressing the challenges of long-tail driving scenarios with low data coverage. * Prototype, validate, and iterate on model architectures using imitation learning, and large-scale data, ensuring robust performance across diverse scenarios. * Perform closed-loop evaluations in sensor simulations and real-world testing environments. * Explore multi-modal and language-conditioned models to broaden the applicability of end-to-end policies, leveraging external data sources and transfer learning to enhance generalization. Qualifications * Currently pursuing a Ph.D. or equivalent experience in Computer Science, Robotics, Engineering, or a related field. * Proficiency in Python for implementing and evaluating research ideas. * Experience with ML frameworks such as PyTorch. * Understanding of version control, testing, and software engineering fundamentals. * Passion for collaborative engineering and building reliable ML systems that support real-world autonomy. Bonus Qualifications * Experience in ML engineering workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization. * Understanding of debugging and profiling on NVIDIA CUDA stack. * Hands-on experience with metrics dashboards, experiment tracking, and ML ops tooling (e.g., Weights & Biases, MLflow, Metaflow). * Hands-on experience working with robotics or real-world sensor data (e.g., video, lidar, IMU, or radar). * Experience in state-of-the-art architectures for object detection and 3D perception. * Familiarity with foundation models, pre-training and efficient fine-tuning, multimodal Transformer architectures, large-scale distributed training. * Experience working with ROS, simulation frameworks (e.g., CARLA, Nvidia DriveSim), or vehicle interfaces. * Experience with robot motion planning techniques like trajectory optimization, sampling-based planning, or model predictive control, or experience with automated driving domains (e.g., perception, prediction, mapping, localization, planning, simulation). Please include links to any relevant open-source contributions or technical project write-ups with your application. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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.

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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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 collaborate with a multidisciplinary team proposing, conducting, and transferring pioneering research at the intersection of Computer Vision, Graphics, and Robotics. You will work with large-scale 2D, 3D, and multimodal datasets, design and train new representation learning methods, and validate ideas in both simulation and physical robotic systems. Your work will aim toward high-impact research publications and contributions to TRI's mission of enabling robots that can seamlessly perceive and adapt to the real world. The Team The Generalizable 3D Representations (G3R) team in the Robotics division is looking for research interns for Summer 2026. We are advancing core 3D perception and representation learning methods, enabling robots to understand, reconstruct, and interact with the world across diverse environments and sensor modalities. Our work spans 3D Foundation Models, Generative Modeling for 3D/4D, Scene and Object Reconstruction, Multi-Modal Policy Learning, and Embodied World Modeling.Our mission is to develop generalizable, data-driven 3D representations that bridge computer vision, graphics, and robotics-capable of adapting to novel environments, capturing the structure of the world, and supporting robust downstream applications in perception, planning, and interaction.Responsibilities Conduct daring research in 3D perception, reconstruction, and representation learning, solving open problems of high theoretical and practical value. Push the boundaries of knowledge in 3D Foundation Models for robotic applications. Collaborate with research scientists and engineers across the G3R team, the Robotics division, TRI, Toyota, and our university partners. Stay up to date with state-of-the-art machine learning, 3D vision, and robotics research. Present your work at internal meetings, top-tier conferences, and through contributions to the broader research community. Qualifications Currently pursuing a Ph.D. in Machine Learning, Computer Vision, Graphics, Robotics, or related fields. Publication record or strong interest in publishing at high-impact venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, CoRL, RSS, ICRA, IROS, SIGGRAPH, RA-L). Passion for large-scale challenges in 3D/4D perception, multimodal foundation models, and physical-world-grounded AI. Proficiency with one or more coding languages and systems, preferably Python, Unix, and a Deep Learning framework (e.g., PyTorch). Ability to collaborate with researchers and engineers to invent and implement novel research ideas. A reliable teammate who loves to think big, dive deep, 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. This is a Summer 2026 paid 13-week internship opportunity. Please note that this internship will be a hybrid in-office role. Human-Centered AI This internship opportunity falls within the Human-Centered AI Division (HCAI). We are an integrated team of ML researchers, behavior scientists, and human-computer interaction experts. At the core of our work, we aim to support people to make better decisions by using the best of big data, technology, and insights about why we do what we do. The Team The Future Product Innovation team is an interdisciplinary team of researchers working at the intersection of generative artificial intelligence (AI), design, engineering, and creativity. We use advances in cognitive modeling, physiological sensing, HCI, and machine learning to support human decision making. Our mission is to accelerate design and engineering processes in the automotive industry. The Internship We are seeking a highly motivated and talented PhD research intern to join our Future Product Innovation team and push the envelope on what is possible with Generative AI technologies in the domain of automotive product design. The ideal candidate will have a strong background in CAD Generation and Machine Learning or related fields, with demonstrated interest in design and generative AI. In this project, the intern will develop 3D shape generation techniques with applications to CAD such as point cloud to CAD and image to CAD. We will match the intern with mentors based on their experience. Over the course of the project, in addition to Future Product Innovation group meetings, the intern will also participate in all Human-Centered AI division meetings and meetings with stakeholders from relevant Toyota business groups. The intern will be exposed to how interdisciplinary industrial research works and learn from our team as well as the other interns in our division. Furthermore, the intern will engage in strategy discussions about how their research connects to business impact at Toyota.Responsibilities In collaboration with your mentor and the other researchers in the department, you will scope the project to align to the core research efforts. Be the primary driver of the technical plan (e.g., model development, analysis plan) with regular feedback from mentors. Execute the project using TRI resources. Present the project's approach and findings in research meetings. Qualifications Currently enrolled in a PhD program in Computer Science, Machine Learning (or related fields). Experience working with CAD data such as B-rep and step-file Experience working with relevant libraries such as pythonocc-core, Shapely, TriMesh, Blender. Experience with deep generative models for CAD generation applications. Track record of executing research projects including publications at top venues including but not limited to CVPR, ICCV, TOG, SIGGRAPH, NeurIPS. Desire to work on challenging open-ended research projects. Demonstrated ability to work autonomously while soliciting feedback. Excellent communication and teamwork skills. Bonus Qualifications Experience with developing research software prototypes. Experience adapting pre-trained models to specific tasks or domains through fine-tuning or similar techniques. Experience with working with CAD development tools. 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 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. The Automated Driving Advanced Development division at TRI will focus on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared commitment. This new division is leading a new cross-organizational project between TRI and Woven by Toyota to conduct research and develop a fully end-to-end learned driving stack. This cross-org collaborative project is harmonious with TRI's robotics divisions' efforts in Diffusion Policy and Large Behavior Models. We are seeking a Senior Simulation Engineer to lead the development of sensor and system-level simulation workflows that support both closed-loop validation and synthetic data generation for training. In this role, you'll help build the simulated environments, data pipelines, and interfaces required to evaluate and improve our full-stack driving policy under diverse, realistic conditions. This role is not limited to simulation infrastructure or tooling. Instead, you will focus on functional validation of learned behaviors, scalable synthetic data generation, and the seamless integration of state-of-the-art simulation technologies to support both training and evaluation workflows. You will also play a key role in driving cross-functional alignment between autonomy, platform, ML infrastructure, and integration teams. This work is part of Toyota's global AI efforts and will be conducted in close collaboration with teams across TRI, Woven by Toyota, and other engineering partners.Responsibilities Build a visually realistic simulator to test full end-to-end autonomy stack behavior, from simulating sensors to motion planning, across a range of scenario conditions. Prototype and integrate with internal and third-party simulators to evaluate their ability to support learned system testing. Curate scenarios, system introspection. Build data logging frameworks used during large-scale virtual tests. Collaborate closely with autonomy, ML, and integration teams to define simulation entry points, runtime configs, and closed-loop evaluation metrics. Build diagnostic tooling and analysis pipelines to understand and improve real system behavior in simulation. Lead cross-functional efforts to close the gap between simulation and on-vehicle deployment, increasing the reliability of sim-based validation. Provide technical mentorship and foster a collaborative, high-trust engineering culture across organizational boundaries. Demonstrate excellent design practices; generate technical documentation; lead technical presentations; aligning with stakeholders before, during, and after implementation is essential. Qualifications Bachelor's or Master's in Computer Science, Robotics, or a related field. 10+ years of experience in robotics, autonomous systems, or simulation. Experience with 3D reconstruction (e.g. Gaussian Splatting, Neural radiance fields, etc). Experience with 3D generation. Experience with Unreal Engine. Strong programming skills in Python and C++, especially for robotics or systems development. Experience with simulation platforms (e.g., CARLA, Applied Intuition, Nvidia DriveSim, etc) and their integration into autonomous system workflows. Knowledge of sensor simulation principles and how perception systems interact with synthetic data. Understanding of end-to-end autonomy pipelines, from raw sensor input to trajectory outputs. Demonstrated ability to design for both users (e.g., autonomy developers) and simulation infrastructure stakeholders. Passion for using simulation to drive real-world progress and system understanding. Bonus Qualifications Hands-on experience validating machine learning-based autonomy stacks in closed-loop simulation. Knowledge of scenario generation, rare event simulation, or counterfactual testing. Knowledge of one or more cloud compute platforms, such as AWS. Experience with multi-agent simulation or high-fidelity 3D environments. Prior experience in fast-paced R&D environments bridging research and production. Please include links to any relevant open-source contributions or technical project write-ups with your application. The pay range for this position at commencement of employment is expected to be between $180,000 and $270,000/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.

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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. This is a summer 2026 paid 12-week internship opportunity. Please note that this internship will be an in-office role. The Mission We are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, our team is building general-purpose machine learning foundation models for dexterous robot manipulation. These models 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 using high-quality simulation to augment real world robot data with procedurally-generated synthetic data. 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 Internship We have several research thrusts under our broad mission, and we are looking for a research intern in any of these areas: Data-efficient and general algorithms for learning robust policies leveraging multiple sensing modalities: proprioception, images, 3D representations, etc. Data annotation and filtering. Improving policies without collecting more data by using non-robotics data at scale, new training objectives, new data annotations, or filtered datasets. Scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video. Structured hierarchical reasoning using learned models Leveraging test time compute for embodied applications Multimodal reasoning models Reinforcement Learning for multimodal models Leveraging history and memory for learning policies for long context tasks. Improving robustness and few-shot generalization by leveraging sub-optimal and self-play data. Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification. The intern who joins our team will be expected to create working code prototypes, interact frequently with team members, run experiments with both simulated and real (physical) robots, and participate in publishing the work to peer-reviewed venues. We're looking for an intern who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data. Qualifications * Experience with machine learning and familiarity with large multimodal datasets and models. OR Hands-on experience with using machine learning for learned control, including RL, offline RL or behavior cloning, for manipulation. * Strong software development skills in Python. * A "make it happen" attitude and comfort with fast prototyping. * A passion for robotics and doing research grounded in important fundamental problems. Bonus Qualifications * Hardware experience. 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. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Team Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from machine learning, optimization, and control theory. We are pursuing a cooperative approach to high-performance driving by developing predictive models and control frameworks for extreme vehicle maneuvering that match or exceed the skills of expert drivers. We envision a world where these tools allow each vehicle to support its driver, creating a safe and enjoyable experience for all. The Internship We are seeking a motivated intern to join our shared control driving team, focusing on cutting-edge research to ensure safe and effective human-AI collaboration for the next generation of advanced driver assistance systems. Potential research areas include developing novel planning and control algorithms to guarantee safety amid challenging driving scenarios, improving performance of existing shared control algorithms under uncertain conditions, and implementing data-driven/ML approaches to shared control with safety guarantees. This role provides an exciting opportunity to explore approaches to human-AI pairing that support safe, intuitive, and responsive shared driving systems. Along the way, you will apply your knowledge to tackle novel research questions and work towards a publication with professional researchers. The internship will be in our headquarters and includes competitive compensation, befitting the challenging but fun nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply.Responsibilities Work with researchers to develop and then undertake a well-scoped research project in a relevant area. Extend existing controls/AI/ML algorithms or design new algorithms for shared control with a human driver at a vehicle's performance limits. Explore approaches to formalize guarantees of safety for shared control algorithms. Implement algorithms on a full-scale vehicle research platform. Publish your original research at a high-impact conference. Qualifications Ph.D. or M.S. student in relevant fields - ML/AI, robotics, computer science, mechanical engineering, aerospace engineering, or similar. Proficient in scientific Python, robotic frameworks (e.g. ROS2.0). Proficiency in machine learning frameworks (e.g. PyTorch) are a plus. Knowledge of nonlinear system control, optimization, and machine learning. Vehicle dynamics knowledge is a plus. Experience working on joint scientific and engineering projects. Familiarity with or interest in racing or high-performance driving is a plus. 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 $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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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 $240,000/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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Team This internship opportunity falls within the Human-Centered AI Division (HCAI). We are an integrated team of ML researchers, behavior scientists, and human-computer interaction experts. At the core of our work, we aim to support people to make better decisions by leveraging the best of big data, technology, and insights about why we do what we do. The Future Product Innovation team is an interdisciplinary team of researchers working at the intersection of generative artificial intelligence (AI), design, engineering, and creativity. We leverage advances in cognitive modeling, physiological sensing, HCI, and machine learning to support human decision making. Our mission is to accelerate design and engineering processes in the automotive industry. The Internship We are seeking a highly motivated and talented PhD research intern to join our Future Product Innovation team and push the envelope on what is possible with Generative AI technologies in the domain of automotive product design. The ideal candidate will have a strong background in Human-Computer Interaction, Artificial Intelligence, or a related field, with demonstrated interest in exploring novel interaction techniques at the intersection of design, generative AI, and human-AI interaction. In this project, the intern will develop new steerable AI systems that enable multi-agent conversation and decision-making support designed to produce actionable engineering and design insights for physical product development. We will match the intern with mentors based on their experience. Over the course of the project, in addition to Future Product Innovation group meetings, the intern will also participate in all Human-Centered AI division meetings. The intern will be exposed to how interdisciplinary industrial research works and learn from our team as well as the other interns in our division. Furthermore, the intern will engage in strategy discussions about how their research connects to business impact at Toyota. Qualifications * Currently enrolled in a PhD program in Human-Computer Interaction, Artificial Intelligence, or a related field. * Demonstrated interest in exploring novel techniques at the intersection of Design, Generative AI, and Human-AI interaction. * Experience prototyping interactive generative AI systems that leverage open-source LLMsExperience designing and conducting user studies, analyzing data, and presenting research findings. * Track record of executing research projects including publications at top HCI conferences such as CHI, UIST, etc. * Desire to work on challenging open-ended research projects. * Demonstrated ability to work autonomously while soliciting feedback. * Excellent communication and teamwork skills. Bonus Qualifications * Experience with modern front-end development frameworks (e.g., React). * Experience with modern LLM frameworks (e.g., LangChain, RAG). * Prior experience developing multi-agent conversational systems, AI collaboration tools, or debate-based interfaces. * Experience adapting pre-trained models to specific tasks or domains through fine-tuning or similar techniques. 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. 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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. The Automated Driving Advanced Development division at TRI will focus on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared commitment. This new division is leading a new cross-organizational project between TRI and Woven by Toyota to conduct research and develop a fully end-to-end learned driving stack. This cross-org collaborative project is harmonious with TRI's robotics divisions' efforts in Diffusion Policy and Large Behavior Models. We are seeking a Senior Simulation Engineer to lead the development of sensor and system-level simulation workflows that support both closed-loop validation and synthetic data generation for training. In this role, you'll help build the simulated environments, data pipelines, and interfaces required to evaluate and improve our full-stack driving policy under diverse, realistic conditions. This role is not limited to simulation infrastructure or tooling. Instead, you will focus on functional validation of learned behaviors, scalable synthetic data generation, and the seamless integration of state-of-the-art simulation technologies to support both training and evaluation workflows. You will also play a key role in driving cross-functional alignment between autonomy, platform, ML infrastructure, and integration teams. This work is part of Toyota's global AI efforts and will be conducted in close collaboration with teams across TRI, Woven by Toyota, and other engineering partners.Responsibilities Build a visually realistic simulator to test full end-to-end autonomy stack behavior, from simulating sensors to motion planning, across a range of scenario conditions. Prototype and integrate with internal and third-party simulators to evaluate their ability to support learned system testing. Curate scenarios, system introspection. Build data logging frameworks used during large-scale virtual tests. Collaborate closely with autonomy, ML, and integration teams to define simulation entry points, runtime configs, and closed-loop evaluation metrics. Build diagnostic tooling and analysis pipelines to understand and improve real system behavior in simulation. Lead cross-functional efforts to close the gap between simulation and on-vehicle deployment, increasing the reliability of sim-based validation. Provide technical mentorship and foster a collaborative, high-trust engineering culture across organizational boundaries. Demonstrate excellent design practices; generate technical documentation; lead technical presentations; aligning with stakeholders before, during, and after implementation is essential. Qualifications Bachelor's or Master's in Computer Science, Robotics, or a related field. 10+ years of experience in robotics, autonomous systems, or simulation. Experience with 3D reconstruction (e.g. Gaussian Splatting, Neural radiance fields, etc). Experience with 3D generation. Experience with Unreal Engine. Strong programming skills in Python and C++, especially for robotics or systems development. Experience with simulation platforms (e.g., CARLA, Applied Intuition, Nvidia DriveSim, etc) and their integration into autonomous system workflows. Knowledge of sensor simulation principles and how perception systems interact with synthetic data. Understanding of end-to-end autonomy pipelines, from raw sensor input to trajectory outputs. Demonstrated ability to design for both users (e.g., autonomy developers) and simulation infrastructure stakeholders. Passion for using simulation to drive real-world progress and system understanding. Bonus Qualifications Hands-on experience validating machine learning-based autonomy stacks in closed-loop simulation. Knowledge of scenario generation, rare event simulation, or counterfactual testing. Knowledge of one or more cloud compute platforms, such as AWS. Experience with multi-agent simulation or high-fidelity 3D environments. Prior experience in fast-paced R&D environments bridging research and production. Please include links to any relevant open-source contributions or technical project write-ups with your application. The pay range for this position at commencement of employment is expected to be between $180,000 and $270,000/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. 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.