PhD Research Intern, Generalist Embodied Agents Research - 2027

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real content. Must not repeat job title. Must not include Job ID etc. Must remove boilerplate like EEO, equal opportunity, scam warning, navigation, cookie, legal, duplicated lines, application instructions. Must preserve all substantive info. We need to parse the posting. Content: - Intro: 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. That's about the role/intro. - What You Will Be Doing: list of duties: 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: list of requirements/qualifications: 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 These are maybe "Qualifications" or "Skills". We need to decide sections. - Then: 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! (maybe part of About the role or Benefits? Not needed.) - 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. Thus we have Pay (hourly rate) and Benefits (Intern benefits). No explicit schedule. - 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. , , JR2025103 We must remove EEO/equal-opportunity boilerplate, application instructions (deadline maybe considered application instruction? The instruction says "Applications for this job will be accepted at least until September 21, 2026." That's an application instruction/deadline. According to rules: remove application instructions. So we should drop that line. Also remove duplicated lines, cookie/navigation/legal/EEO etc. We must preserve all substantive information: So we keep the description, responsibilities, requirements, qualifications, skills, pay, benefits. Also maybe the list of GEAR publications is substantive (they are examples of team's work). Could be part of About the role or maybe a separate section like "Team Highlights"? But we only have allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can put the GEAR publications under About the role (as part of description) or maybe under Qualifications? Probably About the role. We need to avoid filler like "commensurate with experience". Not present. We need to output only HTML fragment, no markdown fences. We'll structure:

About the role

... (intro + mission + team + past projects + Project GR00T + impact + GEAR publications list)

Responsibilities

• ... each duty

Requirements

Maybe combine qualifications and skills? But we have both Requirements and Qualifications and Skills headings allowed. We need to decide what goes where. Typically Requirements = minimum qualifications (PhD, etc). Qualifications = preferred or additional. Skills = technical skills. We can split. Let's extract: Minimum requirements: - 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. Then under Multimodal Foundation Model and Robotics sub-bullets: these are more detailed expectations; could be under Qualifications. Qualifications: - 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. - 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. Skills: maybe list of frameworks: PyTorch, Jax, Tensorflow, Python, C++, CUDA, etc. But we already covered some. Could separate. But we must not create thin sections. Perhaps combine Requirements and Qualifications into one section? But we have headings allowed; we could use Requirements for the core, and Skills for technical proficiencies. Qualifications maybe not needed if we can incorporate into Requirements. But we need to follow instruction: "Prefer a few substantive sections over many thin ones." So we should avoid too many sections. Maybe we use About the role, Responsibilities, Requirements (which includes qualifications and skills), Benefits, Pay. That's 5 sections. We must not create Schedule unless present; not present. Thus sections: About the role, Responsibilities, Requirements, Benefits, Pay. Now we need to ensure we include all substantive info. Let's craft About the role paragraph: 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. The team’s notable publications include 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. That covers GEAR publications. Now Responsibilities list: - 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. Now Requirements section: we need to include PhD pursuit, engineering skills, large-scale ML/AI systems, experience with multimodal foundation model or robotics, plus the detailed expectations (hands-on training, publications, understanding kinematics, etc.), plus proficiency in Python (required) and C++/CUDA (plus). Also maybe mention familiarity with physics simulation frameworks. We'll put as

• ... each bullet. We need to avoid repeating "etc." but it's fine. Now Benefits: "You will also be eligible for Intern benefits." That's vague but it's substantive: Intern benefits. We can include that as a

  maybe. Pay: "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." We'll put that as

  . We must not include application deadline, EEO, etc. Now ensure we don't repeat job title. Not included. Now output HTML fragment. Let's craft. Check for any leftover boilerplate: "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!" This is somewhat fluff but still substantive? It's more marketing. Could be considered part of About the role? It's not essential but it's not boilerplate like EEO. It's okay to keep maybe in About the role. But we already have a lot. Could add a sentence: "NVIDIA is widely considered to be one of the technology world's most desirable employers, with forward-thinking and productive people." Might be okay. But we must not invent or summarize away detail. It's okay to keep. We'll incorporate that into About the role after mission. Now final HTML:

  About the role

  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