PhD Research Intern, Generalist Embodied Agents Research - 2027
Nvidia
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Practise the PhD Research Intern, Generalist Embodied Agents Research - 2027 at Nvidia interview free →NVIDIA is searching for an outstanding research intern to build humanoid robot foundation models and systems in the Generalist Embodied Agent Research (GEAR) group. Everything that moves will eventually be autonomous. Our mission is to build general-purpose embodied agents that learn to explore and master complex skills across the virtual and the physical world. You will work with an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, game AI, and physical simulation. Our past projects include Eureka , VIMA , Voyager , MineDojo , MimicPlay , Prismer , and more. One of our team’s most recent milestones includes Project GR00T , a foundation model for humanoid robots. Your contributions will have a significant impact on our moonshot research projects and product roadmaps. What you will be doing: Design and implement novel AI algorithms and models for general-purpose humanoid robots and embodied agents; Develop large-scale AI training and inference methods for foundation models; Optimize and deploy AI models in physical simulation and on robot hardware; Collaborate with research and engineering teams across all of NVIDIA to transfer research to products and services. What we need to see: Pursuing a PhD degree in Computer Science/Engineering, Electrical Engineering, etc. Outstanding engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow, etc.). Python is required; C++ and CUDA proficiencies are a plus. Excellent skills in working with large-scale machine learning/AI systems and computer infrastructure. Experience with at least one of the following areas: multimodal foundation model or robotics. Multimodal Foundation Model: Hands-on training experience and publications in at least one of the following models: LLMs, vision-language models, video generative models, diffusion models, and action-based transformers. Robotics: Hands-on training experience and publications in robot learning, such as reinforcement learning, imitation learning, classical control methods, etc. Deep understanding of robot kinematics, dynamics, and sensors; Ability to safely operate robot hardware, lab equipment, and tools; Knowledge of control methods, such as PID, MPC, whole body control, etc; Familiarity with physics simulation frameworks such as Mujoco and Isaac suite. GEAR Publication: DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data DreamZero: World Action Models are Zero-shot Policies SONIC: Supersizing motion tracking for natural humanoid whole-body control NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and embodied agents! Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD - 94 USD.
 You will also be eligible for Intern benefits . Applications for this job will be accepted at least until September 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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Listed on workday · posted 2026-10-30. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.