Graduate research assistant jobs in Berkeley, CA - 3,066 jobs

### As a research scientist with Martian, you will develop new techniques to understand how AI models work. This work will focus on exploring and improving a technique we call “model mapping”: converting transformers into more interpretable representations (such as programs). We are looking for people who can develop and scale up methods for making transformers more interpretable through model mapping and then understanding the transformers in the new domain we map to. Full details can be found here. #J-18808-Ljbffr

A leading AI technology company in San Francisco is seeking a Research Scientist to advance AI models and techniques. You'll work in a collaborative environment, focusing on novel research, and applying AI solutions to real-world challenges. Candidates with a Bachelor's or Master's degree and 2+ years of relevant experience are encouraged to apply, with a competitive salary range of $192,000 - $260,000. #J-18808-Ljbffr

A leading AI robotics firm based in San Francisco is seeking an AI Robotics Research Scientist. This role involves developing and training robotic AI models and working with an all-star team to tackle advanced robotics challenges. The ideal candidate will have a Ph.D. in Robotics or Computer Science and experience in deep learning and robotic hardware. A competitive salary range of $180,000 - $250,000 plus equity is offered, along with strong benefits that include paid time off, health insurance, and 401k contributions. #J-18808-Ljbffr

About Nudge Nudge's goal is to help the brain work better by creating a generalized product that can precisely stimulate and image the brain, entirely non-invasively. We aim to achieve this by developing cutting-edge ultrasound technology to treat neurological and psychiatric disorders, like addiction, and eventually, creating a mainstream consumer device that can modulate mood, focus, sleep, and more. To realize those ambitions, we're growing a scrappy, multidisciplinary, science and engineering team focused on making the best technology possible for interfacing with the whole brain, and a product that has the potential to improve people's daily lives more than any other. About the team The Research Team at Nudge is innovating on multiple frontiers in neuroscience and neurotechnology, and is primarily focused on developing ultrasound-based neuromodulation to treat conditions like depression, chronic pain and addiction as well as enhance the wellbeing of healthy people. We're also building the first scalable, portable hardware for noninvasive structural ultrasound-based imaging the quality of an MRI. The team is running human trials for neuromodulation and developing algorithms that will enable on-device imaging. About the role Work closely with the Head of Research and engineering team to build the capabilities for on-device ultrasound-based imaging. Develop algorithms for structural and functional ultrasound-based imaging Perform validation of in-silico ultrasound imaging methods with Nudge hardware in physical models and in vivo Contribute to the development of aberration correction techniques informed by ultrasound-based imaging About you 5+ years experience PhD or Postdoc in Bioengineering, Medical Imaging, Physics or equivalent Expertise in ultrasound physics and metrology Demonstrated history of exceptional contributions in your prior work experiences Expertise in one or more of: Full-waveform inversion imaging Functional transcranial doppler imaging Functional ultrasound imaging Machine learning experience a plus Compensation $140,000 - $230,000/year + equity Your salary may vary depending on multiple factors such as job-related knowledge, skills, and experience. #J-18808-Ljbffr

About the Team The Strategic Deployment team makes frontier models more capable, reliable, and aligned to transform high-impact domains. On one hand, this involves deploying models in real-world, high-stakes settings to drive AI-driven transformation and elicit insights-training data, evaluation methods, and techniques-to shape our frontier model development. On the other hand, we leverage these learnings to build the science and engineering of impactful frontier model deployment. As a key element of this effort, OpenAI for Science aims to harness AI to accelerate the process of scientific research. This involves building models and an AI-powered platform that speeds up discovery and helps researchers everywhere do more, faster. About the Role As a Research Scientist focused on the mathematical sciences, you will help build models, tools, and workflows that move theoretical research-in fields such as mathematics, theoretical physics, and theoretical computer science-forward. You\'ll design domain-specific data and signals, shape training and evaluation, guide how to wire models to scientific tools, and work with the academic community to speed up adoption and impact. We\'re looking for people who... Hold a current or recent academic position in mathematical sciences (mathematics, theoretical physics, theoretical computer science) or a related field Regularly use frontier models in their own research Move easily between theory and code, and are eager to contribute technically as well as academically Either know or are eager to learn modern AI and run AI experiments end-to-end Are strong scientific communicators Care about rigor and reproducibility in scientific results This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Assist in designing and building frontier AI models that are great at solving frontier mathematical sciences problems Build high-quality scientific datasets and synthetic data pipelines (symbolic, numeric, and simulator-based) Design reinforcement and grading signals for physics and run reinforcement learning/optimization loops to improve model reasoning Define and run evals for scientific reasoning, derivations, simulations, and literature grounding; track progress over time Partner with research labs and the academic community Drive adoption of frontier AI within the scientific community Uphold high standards for safety, data governance, and reproducibility You might thrive in this role if you Are passionate about pushing the boundaries of your field using AI Have used ChatGPT to do calculations and prove or improve lemmas in your field of study Communicate clearly to both scientists and AI engineers; you like collaborating across teams and with academia Nice to have Open-source contributions to mathematical science or AI tooling Experience building or curating domain datasets and benchmarks Experience engaging a research community (teaching, workshops, tutorials, standards) About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI\'s Affirmative Action and Equal Employment Opportunity Policy Statement. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link. OpenAI Global Applicant Privacy Policy At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology. Compensation Range: $380K - $460K #J-18808-Ljbffr

A cutting-edge robotics startup is looking for a Research Scientist to enhance their robotic manipulation systems. This role entails advancing research, collaborating on publications, and prototyping solutions within a multi-disciplinary team. The ideal candidate has a strong grasp of modern robotic methods and 5+ years of relevant experience, alongside a solid publication record in prestigious conferences. Compensation ranges from $160,000 to $210,000 annually, with equity options available. #J-18808-Ljbffr

A pioneering AI company in San Francisco is seeking a talented AI Researcher to push the boundaries of custom AI research and model training. You will lead experiments in model architectures and fine-tune techniques for efficiency, collaborating with a skilled team. Ideal candidates have a strong background in training with PyTorch and experience in optimizing LLMs. This role offers competitive compensation ranging from $250K to $350K, along with equity and benefits. #J-18808-Ljbffr

Substrate is addressing one of the most important technological problems facing the United States. At the intersection of advanced manufacturing and cutting‑edge physics, we are developing technologies that will reshape the semiconductor industry and strengthen America's technological leadership. We are a team of world‑class scientists, engineers, and technical experts building technology for the United States. Summary As a Research Scientist working with AI, you will accelerate and augment R&D workflows by applying machine learning to scientific simulations and modeling while simultaneously building internal AI capabilities across the organization. This role sits at the intersection of cutting‑edge physics and artificial intelligence, and you'll work hands‑on to develop AI‑augmented tools that enable breakthrough research, and build the infrastructure and expertise that empowers our technical teams to leverage AI in their own work. Whether you are a physicist who has embraced machine learning or an AI expert with deep scientific domain knowledge, you will play a pivotal role in defining how we utilize AI to accelerate our own internal R&D. Responsibilities Integrate machine learning techniques to accelerate scientific simulations, modeling, and computational workflows Develop AI‑augmented tools for materials science, device physics, or accelerator physics applications Build internal AI infrastructure and capabilities to enable research teams across the organization Train and mentor scientists and engineers on integrating AI/ML into their research workflows Implement surrogate models, physics‑informed neural networks, or generative approaches for scientific problems Develop data pipelines and frameworks for scientific machine learning across distributed teams Collaborate with computational physicists and experimentalists to identify high‑impact AI applications Set AI best practices and establish standards for ML‑augmented R&D Required Qualifications 5+ years professional or academic research experience in physical sciences, engineering, or related field 2‑3+ years hands‑on experience applying machine learning to scientific or technical problems Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, JAX, or similar) Deep understanding of scientific computing, numerical methods, and computational modeling Proven ability to translate scientific problems into machine learning approaches Experience building tools, infrastructure, or capabilities used by technical teams Preferred Qualifications PhD in Physics, Materials Science, Computer Science, Applied Mathematics, or related field Publications applying ML to scientific computing, simulation, or experimental data analysis Experience with physics‑informed machine learning or scientific foundation models Background in accelerator physics, semiconductor devices, materials modeling, or related domains Track record of enabling technical teams through tool development or mentorship Salary Range $150,000-$400,000 USD Substrate is an equal opportunity employer. It provides equal employment opportunity to all applicants without regard to race, color, religion, national origin, disability, medical condition, marital status, sex, gender, age, military or veteran status, or any other characteristic protected by applicable federal, state, or local laws. Substrate will provide reasonable accommodations to applicants with disabilities. If you need an accommodation during the hiring process, please let your recruiter know. Applicants must be legally authorized to work in the United States. This position is not eligible for visa sponsorship. #J-18808-Ljbffr

A generative media company in San Francisco seeks a Research Scientist to lead innovation in video generation. Responsibilities include developing model compression techniques and optimizing for efficiency. The ideal candidate has a PhD or relevant industry experience in Machine Learning, particularly with diffusion models. The role offers competitive compensation, benefits, and an inspiring startup culture. #J-18808-Ljbffr

About P-1 AI: We are building an engineering AGI. We founded P-1 AI with the conviction that the greatest impact of artificial intelligence will be on the built world-helping mankind conquer nature and bend it to our will. Our first product is Archie, an AI engineer capable of quantitative and spatial reasoning over physical product domains that performs at the level of an entry‑level design engineer. We aim to put an Archie on every engineering team at every industrial company on earth. Our founding team includes the top minds in deep learning, model‑based engineering, and industries that are our customers. We just closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.). About the Role: We're seeking an exceptional AI Research Scientist to help us push the boundaries of AI applied to the physical world. This role blends cutting‑edge AI research with hands‑on engineering, and is ideal for someone who thrives at the intersection of ideas and implementation. You'll be leading projects that develop agentic AI systems designed to solve real‑world mechanical, electrical, and aerospace engineering problems-systems that think, remember, act, and adapt. This is not a “pure research” position: we're looking for a hacker‑scientist hybrid-someone who's published in top venues but is not afraid of any layer in the tech stack. What You'll Do: Design and implement agentic systems that autonomously solve physical engineering tasks. Develop advanced memory, retrieval, and planning architectures for LLM‑based agents. Apply (or invent) reinforcement learning strategies for reasoning, planning, and online adaptation. Contribute to both research strategy and technical implementation-this is a hands‑on role. Collaborate with a small, elite team of researchers and engineers across domains. Stay on the edge of what's possible and bring promising ideas into reality. About you: Have experience at the frontier of AI research (e.g., LLMs, RL, memory systems, agent architectures). Are passionate about applied problems-especially in mechanical, aerospace, or electrical engineering domains. Are fluent in Python and major ML/AI frameworks (PyTorch, JAX, etc.). Thrive in fast‑moving environments and feel comfortable working towards underspecified goals. Have a “whatever it takes” mindset: you're the kind of person makes things work. Can go from whiteboard to working prototype without waiting for someone else to “engineer” it. Preferred Qualifications: PhD in Computer Science, Robotics, Engineering, Math, or a related technical field (or equivalent experience). Relevant publications in top‑tier venues of your field. Experience with physical engineering domains a plus. Familiarity with agent tool‑use, retrieval‑augmented generation, or long‑term memory systems. Deep knowledge of reinforcement learning algorithms and practical challenges. Interview process: Initial screening - Head of Talent (30 mins) Hiring manager interview - Head of AI (45 mins) Technical Interview - AI Chief Scientist (45 mins) Culture fit / Q&A (maybe in person) - with co‑founder & CEO (45 mins) #J-18808-Ljbffr

We are Genmo, a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Join us in shaping the future of AI and pushing the boundaries of what's possible in video generation. Key responsibilities Lead research initiatives in advanced diffusion models for text-to-video generation, focusing on improving visual quality, temporal consistency, and semantic fidelity Develop and implement state-of-the-art algorithms for translating textual descriptions into dynamic video content Design and conduct rigorous experiments to validate new ideas and evaluate model performance Collaborate with cross-functional teams to integrate research breakthroughs into our production pipeline Stay at the cutting edge of the field by regularly reviewing academic literature and attending top-tier conferences Contribute to the research community through high-quality publications and open-source contributions Mentor junior researchers and foster a culture of innovation within the research team Work closely with product teams to align research directions with user needs and market opportunities Qualifications Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field Must have: Strong publication record in top-tier conferences (e.g., CVPR, ICCV, NeurIPS, ICML) with a focus on generative models, particularly diffusion models Extensive experience implementing and optimizing large-scale generative models for image or video tasks Deep understanding of state-of-the-art techniques in text-to-image and text-to-video generation Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow Excellent communication skills with the ability to explain complex technical concepts to diverse audiences Proven ability to work collaboratively in a team environment Ideal candidate will have: Postdoctoral or industrial research experience in generative AI for video Hands-on experience with text-to-video generation projects Expertise in other generative model architectures (e.g., GANs, VAEs) and their applications to video Experience working with large-scale datasets and distributed computing environments Track record of successful collaboration with product teams on technology transfers Familiarity with video codecs, compression techniques, and perceptual quality metrics Contributions to open-source projects in the field of generative AI Additional information The role is based in the Bay Area (San Francisco). Candidates are expected to be located near the Bay Area or open to relocation. Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish. #J-18808-Ljbffr

Virtue AI is at the forefront of AI security & compliance. Our mission is to build the essential AI security platform with advanced and comprehensive guardrails and red‑teaming tools that enable organizations to deploy different AI applications confidently and responsibly in different sectors, such as finance, healthcare, telecom, retail, and government. Just as Palo Alto Networks redefined network security, our mission is to define and lead the new category of AI Security. We are a well‑funded, early‑stage startup founded by industry veterans, and we're looking for passionate builders to join our core team. Are you a high‑performing, motivated machine learning engineer ready to make a significant impact in the AI security space? We are looking for talented engineers to develop cutting‑edge products on agent and LLM securities. What You'll Do As a Research Scientist, you will play a key role in developing production‑ready and cutting‑edge agent and ML security techniques. Your work will directly contribute to advancing our products and services and driving innovation within the industry. You will: Develop our core techniques for agent and model red‑teaming, including discovering novel testing paths, designing novel testing techniques, and developing automatic testing platforms Develop and train our core guardrail models for different input modalities and defense targets and goals Apply efficiency inference methods to reduce model latency Work with the research engineers to integrate our developed techniques into products What Makes You a Great Fit You'll thrive in this role if you're excited by new technology, love solving customer problems, and can comfortably bridge the business and technical worlds. Required qualifications: Proficiency in programming languages such as Python, along with expertise in LLM libraries like PyTorch, DeepSpeed, OpenRLHF, vLLM, verl, etc Experience in LLM finetuning for different modalities Experience in building LLM‑based agents for various applications Experience in conducting large‑scale red‑teaming for LLMs and agents Preferred qualifications: Hands‑on experience with Docker for containerization and deployment Hands‑on experience in backend engineering (Go, C/C++) and front‑end development (Node.js, Typescript) Enthusiasm for thriving in a fast‑paced startup environment Strong problem‑solving skills and effective communication abilities Why Join Virtue AI Competitive base salary compensation + equity commensurate with skills and experience. Impact at scale - Help define the category AI security and partner with Fortune 500 enterprises on their most strategic AI initiatives. Work on the frontier - Engage with bleeding‑edge AI/ML and deploy AI security solutions for use cases that don't yet exist anywhere else yet. Collaborative culture - Join a team of builders, problem‑solvers, and innovators who are mission‑driven and collaborative. Opportunity for growth - Shape not only our customer engagements, but also the processes and culture of an early lean team with plans for scale. Equal Opportunity Employment Virtue AI is an Equal Opportunity Employer. We welcome and celebrate diversity and are committed to creating an inclusive workplace for all employees. Employment decisions are made without regard to race, color, religion, sex, gender identity or expression, sexual orientation, marital status, national origin, ancestry, age, disability, medical condition, veteran status, or any other status protected by law. We also provide reasonable accommodations for applicants and employees with disabilities or sincerely held religious beliefs, consistent with legal requirements. #J-18808-Ljbffr

A VC-backed AI simulation platform in San Francisco is seeking a Behavioral Research Scientist to shape AI agents' cognitive foundations. The role focuses on modeling decision-making processes, translating theories into practical frameworks, and conducting experiments to enhance simulation realism. Ideal candidates will have a PhD in relevant fields and experience in behavioral modeling. Join a passionate team making a real-world impact in AI technology. #J-18808-Ljbffr

Who We Are At TwelveLabs, we are pioneering the development of frontier multimodal foundation models that can see, hear and understand the world as humans do. Our models have redefined the standards in video-language modeling, allowing developers to build programs with state-of-the-art semantic search, summarization and analysis capabilities. TwelveLabs has raised $107 million in Seed + Series A funding from world-class VC & corporate partners: NVIDIA, NEA, Radical Ventures, Index Ventures, Snowflake and Databricks. Our advisory team features AI visionaries and founders such as Fei-Fei Li, Silvio Savarese, Alexandr Wang and more. Headquartered in San Francisco, with an influential APAC presence in Seoul, our global footprint underscores our commitment to driving worldwide innovation. About the Science Team The Science team is at the forefront of multimodal AI research, tackling the most critical technical challenges in video understanding. Our core research areas include video embedding and search, multimodal language models capable of reasoning over video content, and intelligent agents that can interact with and analyze video data. We go beyond academic research: our goal is to ensure that research outcomes are directly integrated into products and platforms, delivering real value to users. We work closely with the Engineering and Product teams and foster a collaborative culture centered around open communication and dynamic idea exchange. About the Role As a Research Scientist, you will play a key role in driving TwelveLabs' core technology research and helping define its direction. You'll conduct pioneering work in video understanding, multimodal learning, and AI agents; identifying critical research problems, designing innovative solutions, and running effective experiments. This also involves developing data strategies and defining evaluation methodologies. You will lead finetuning efforts for video embedding and video language models, closely collaborating with the MLE and Solutions Engineering team to productionize finetuning efforts. You'll collaborate closely with team leads, fellow scientists and researchers, clearly communicating your findings and contributing to TwelveLabs' broader research roadmap and culture. What Makes This Role Unique at TwelveLabs TwelveLabs takes a focus-and-collaborate approach to tackling complex video AI challenges. Rather than solving isolated problems, we work together as a unified team toward the broader goal of understanding video. Our research philosophy strikes a balance between rigorous scientific experimentation and real-world application. We aim to build multimodal systems that are not only powerful, but also trustworthy and interpretable. Open communication and mutual learning are central to our culture, enabling us to quickly evolve ideas and pursue the most impactful research directions. These align closely with our core values: integrity, growth mindset, and tenacity. You Might Be a Great Fit If You Have We're looking for candidates with strong research experience in areas like video (multimodal) understanding, large language models, domain adaptation, representation learning, or action recognition; especially where those align with our mission. Your experience should be supported by past projects, your contributions, and related publications. You should be capable of independently leading research projects from ideation to execution. Strong proficiency in Python and Pytorch is essential. Excellent written and verbal communication in Korean as well as English is a bonus. A Phd or Masters Degree in addition to significant research experience in computer science, AI, or related fields. Additional experience developing and deploying large-scale ML models in production, or optimizing large model training, is a major plus. Even if there are a few checkboxes that aren't ticked through your prior experience, we still encourage you to apply! If you are a 0-1 achiever, a ferocious learner, and a kind and fun team player who motivates others, you will find a home at TwelveLabs. We are a global company that values the uniqueness of each person's journey. It is the differences in our cultural, educational, and life experiences that allow us to constantly challenge the status quo. We are looking for individuals who are motivated by our mission and eager to make an impact as we push the bounds of technology to transform the world. Join us as we revolutionize video understanding and multimodal AI. Benefits and Perks: 🤝 An open and inclusive culture and work environment. 🧑💻 Work closely with a collaborative, mission-driven team on cutting-edge AI technology. 🦷 Full health, dental, and vision benefits. ✈️ Flexible PTO and parental leave policy. Office closed the week of Christmas and New Years. 🛂 VISA support (such as H1B and OPT transfer for US employees). #J-18808-Ljbffr

About Sygaldry Sygaldry Technologies is building quantum-accelerated AI servers to exponentially speed up training and inference for AI. By integrating quantum and AI, we're accelerating the path to superintelligence, and engineering the conditions for it to scale efficiently and operate affordably. Sygaldry AI servers combine multiple qubit types within a single, fault-tolerant architecture to deliver the combination of cost, scale, and speed necessary for advanced AI applications. We pioneer new domains in physics, engineering, and AI, tackling the hardest challenges with a grounded, optimistic, and rigorous culture. We're looking for individuals ready to define the intersection of quantum and AI and drive its profound global impact. About the Role Generative AI is transforming what's computationally possible-but it's also exposing the limits of classical hardware. Diffusion models produce extraordinary results, yet their iterative sampling and high-dimensional score estimation create computational bottlenecks that scale poorly. We believe quantum computing offers a path through these bottlenecks. As an ML Research Scientist, you'll work at the frontier of generative modeling and quantum acceleration, developing the theoretical foundations and practical implementations that connect these fields. You'll identify where quantum approaches can provide genuine advantage in generative workflows-not incremental improvements, but structural speedups rooted in the mathematics of these models. What You'll Work On Generative Model Architecture & Efficiency Advance state-of-the-art diffusion and score-based generative models Analyze computational bottlenecks in sampling, denoising, and likelihood estimation Develop and benchmark novel solver methods for diffusion ODEs/SDEs Quantum-Classical Integration Identify mathematical structures in generative models amenable to quantum speedup Prototype hybrid workflows where quantum subroutines accelerate classical pipelines Rigorously benchmark theoretical versus practical advantage in realistic workloads Research to Production Translate research insights into scalable implementations Collaborate with quantum hardware teams to inform architecture requirements Build systems that make quantum-accelerated generation accessible to practitioners You May Be a Good Fit If You Have deep expertise in diffusion probabilistic models, score matching, or related generative methods Understand the mathematical foundations: SDEs, ODEs, Langevin dynamics, probability flow Are experienced with ML frameworks (PyTorch, JAX) and efficient inference implementation Question assumptions and validate with rigor, following interesting threads wherever they lead Communicate complex ideas clearly across research communities Are excited to work on problems no one has solved before Strong Candidates May Have Published research on diffusion models, score-based generation, or neural ODE/SDE methods Experience optimizing sampling efficiency (DDIM, DPM-Solver, consistency models, etc.) Familiarity with numerical methods for differential equations Understanding of quantum algorithms and computational complexity Background in high-dimensional probability or stochastic processes Why This Matters Your work accelerates the path to quantum superintelligence. Each quantum component integrated, each AI model enhanced, each instruction set optimized brings us closer to a future where intelligence and quantum mechanics are inextricably intertwined. We're not building incremental improvements - we're creating exponential transformations that will make AI more affordable, sustainable, personalized, and fundamentally more capable. How We're Different We're building the infrastructure for quantum superintelligence and pioneering new domains at the intersection of physics, engineering, and AI. At Sygaldry, curiosity and intellectual courage drive our work. We approach ambitious challenges with a grounded, optimistic, and rigorous culture and know that kind people build the strongest teams. We prioritize mission over ego and collaborate openly with a strong sense of shared purpose. We dream big, yet we execute with a love of detail. We're looking for scientists, engineers, and operators to forge new paths with us at the intersection of quantum and AI. Culture & Benefits Visa Sponsorship - We know what it takes to make top talent thrive here. We're open to supporting visas whenever possible. Compensation - We value your contribution and invest in your future with a competitive salary and meaningful equity. Benefits - Your well-being matters. We provide company-sponsored health coverage to give you and your family peace of mind. Connection - Whether it's company offsite or casual crew socials, we make time to connect, recharge, and have fun together. Time Off - We trust you to take the time you need. Unlimited PTO so you can rest, recharge, and come back ready to make an impact. We encourage applications from candidates with diverse backgrounds. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. We encourage you to apply even if you do not believe you meet every single qualification. If you don't think this role is right for you, but you believe that you would have something meaningful to to contribute to our mission, please reach out at ********************** #J-18808-Ljbffr

We are seeking a talented Research Scientist specializing in generative modeling and diffusion models to join our modeling team. This role is ideal for someone who is an expert at pre-training or post-training of large-scale diffusion models for images, videos, or 3D assets or scenes. You will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds Develop and experiment with post-training for large-scale diffusion models to add novel control signals, adapt to target aesthetic preferences, or distill for efficient inference Collaborate closely with research and product teams to understand and translate product requirements into effective technical roadmaps. Contribute hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment. Continuously explore and integrate cutting-edge research in diffusion and generative AI more broadly Act as a key technical resource within the team, mentoring colleagues, and driving best practices in generative modeling and ML engineering Ideal Candidate Profile 3+ years of experience in generative modeling or applied ML roles, ideally at a startup or other fast-paced research environment Extensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of diffusion models and other generative models Deep expertise in at least one area of generative modeling: pre-training, post-training, diffusion distillation, etc for diffusion models Strong history of publications or open-source contributions involving large-scale diffusion models Strong coding proficiency in Python and experience with GPU-accelerated computing. Ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes. Comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation. Nice to Have Contributions to open-source projects in the fields of computer vision, graphics, or ML. Familiarity with large-scale training infrastructure (e.g., multi-node GPU clusters, distributed training environments). Experience integrating machine learning models into production environments. Led or been involved with the development or training of large-scale, state-of-the-art generative models #J-18808-Ljbffr

Join our core R&D team building end-to-end automated research systems. 📰 The 1st fully AI-generated scientific discovery to pass the highest level of peer review - the main track of an A* conference (ACL 2025). ************************************** Key Responsibilities Design & implement novel architectures for automated research. Collaborate with a focused group of researchers tackling problems at the forefront of long‑horizon agentic capabilities, post‑training for open‑ended goals, and environment development. Publish internal key‑findings along with external collaboration success stories. Qualifications PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree. Proven track‑record of high‑impact AI/ML research contributions in either the academic or corporate settings. Expertise in developing long horizon. multi‑agent systems and/or model post‑training, with a focus on capabilities. Even better if built for scientific domains and/or open‑ended discovery purposes. Passion for accelerating the process of problem‑solving & scientific discovery, with comfort in high‑autonomy roles & environments. Our Culture Competitive salary & equity packages. Unlimited PTO with a focus on on‑site team‑building & communal work environment. Conference attendance & involvement in community‑facing events. High‑agency & responsibility. #1: We are a small, dedicated group of top investors, researchers, and industry veterans, dedicated to the mission of accelerating discovery. Join us. #J-18808-Ljbffr

We are building an engineering AGI. We founded P-1 AI with the conviction that the greatest impact of artificial intelligence will be on the built world-helping mankind conquer nature and bend it to our will. Our first product is Archie, an AI engineer capable of quantitative and spatial reasoning over physical product domains that performs at the level of an entry‑level design engineer. We aim to put an Archie on every engineering team at every industrial company on earth. Our founding team includes the top minds in deep learning, model‑based engineering, and industries that are our customers. We just closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.). About the Role: We're seeking an exceptional AI Research Scientist to help us push the boundaries of AI applied to the physical world. This role blends cutting‑edge AI research with hands‑on engineering, and is ideal for someone who thrives at the intersection of ideas and implementation. You'll be leading projects that develop agentic AI systems designed to solve real‑world mechanical, electrical, and aerospace engineering problems-systems that think, remember, act, and adapt. This is not a “pure research” position: we're looking for a hacker‑scientist hybrid-someone who's published in top venues but is not afraid of any layer in the tech stack. What You'll Do: Design and implement agentic systems that autonomously solve physical engineering tasks. Develop advanced memory, retrieval, and planning architectures for LLM‑based agents. Apply (or invent) reinforcement learning strategies for reasoning, planning, and online adaptation. Contribute to both research strategy and technical implementation-this is a hands‑on role. Collaborate with a small, elite team of researchers and engineers across domains. Stay on the edge of what's possible and bring promising ideas into reality. About you: Have experience at the frontier of AI research (e.g., LLMs, RL, memory systems, agent architectures). Are passionate about applied problems-especially in mechanical, aerospace, or electrical engineering domains. Are fluent in Python and major ML/AI frameworks (PyTorch, JAX, etc.). Thrive in fast‑moving environments and feel comfortable working towards underspecified goals. Have a “whatever it takes” mindset: you're the kind of person makes things work. Can go from whiteboard to working prototype without waiting for someone else to “engineer” it. Preferred Qualifications: PhD in Computer Science, Robotics, Engineering, Math, or a related technical field (or equivalent experience). Relevant publications in top‑tier venues of your field. Experience with physical engineering domains a plus. Familiarity with agent tool‑use, retrieval‑augmented generation, or long‑term memory systems. Deep knowledge of reinforcement learning algorithms and practical challenges. Interview process: Initial screening - Head of Talent (30 mins) Hiring manager interview - Head of AI (45 mins) Technical Interview - AI Chief Scientist (45 mins) Culture fit / Q&A (maybe in person) - with co‑founder & CEO (45 mins) #J-18808-Ljbffr

AI Researcher ai Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building. Join us at the cutting edge, where we're scaling generative transformer diffusion models, designing next-gen benchmarks, and engineering foundation models that go far beyond LLMs. You'll be at the core of a moonshot journey to define what's next in agentic AI and frontier model capabilities. We are looking for an experienced AI Researcher who is eager to advance the frontier of AI, help us design, build, and scale end-to-end novel foundation models, and leverage their hands‑on experience implementing a wide range of pre‑training and post‑training models, including large foundation models (beyond just LLM fine‑tuning). Who are we? Hum is a seed‑funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we're backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations. What do we do? We're building multimodal foundation models for the natural world. We believe there's more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real‑world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world. The role will involve: Research & Design: Deep understanding of current machine learning research. Proven track record of generating new ideas or enhancing existing ones in machine learning, evidenced by first‑author publications or projects. Contribute to research that uncovers the semantics of large datasets, with a focus on earth observation and remote sensing data. Ability to independently manage and execute a research agenda, selecting impactful problems and conducting long‑term projects autonomously. Implementation: Developing high‑level proof‑of‑concept (POC) models. Experimenting with new state‑of‑the‑art techniques to surpass existing models. Plan and execute innovative research and development to push the boundaries of current technology. Writing and Publication: Assisting in the preparation and writing of technical and scientific papers for publication. Demonstrated strong scientific communication/presentation skills. Requirements PhD degree in computer science, engineering, a related field, or equivalent experience. Proven track record of successful machine learning research projects. 5+ years of experience in relevant jobs. Strong scientific understanding of the field of generative AI. Location wise, strong preference for in‑person in San Francisco. We are an entirely in‑person team, but are willing to consider remote for exceptional candidates. Nice to have Proficiency in scripting languages such as Python, Bash, or PowerShell. Demonstrated experience with deep learning and transformer models. Familiarity with designing, training, and fine‑tuning large models. Proficiency in frameworks like PyTorch or TensorFlow. Strong technical engineering skills. Previous experience in creating high‑performance implementations of deep learning algorithms. Team player, willing to undertake various tasks to support the team. #J-18808-Ljbffr