PhD Research Intern, Generalist Embodied Agents Research - 2027

NVIDIA is hiring a PhD Research Intern, Generalist Embodied Agents Research - 2027 in Santa Clara, United States. It pays $38-$94/hr and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions PyTorch, TensorFlow and JAX among its tools and skills.
Level classes it as an internship.
NVIDIA has 2,700+ other open roles on Level.

AI in this role

PyTorchTensorFlowJAX

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 expected hourly rate for this position is 38 USD – 94 USD.

You will also be eligible for Intern benefits.

Applications for this job will be accepted at least until November 3, 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.

How we rate this

PhD Research Intern, Generalist Embodied Agents Research - 2027 at NVIDIA rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

PhD Research Intern, Generalist Embodied Agents Research - 2027 is an open job at NVIDIA.
Level rates this role AI Level 4 of 4: Builds AI.
The listed pay is $38-$94/hr.
The role is based in US, CA, Santa Clara.
The job was posted on September 17, 2026.
Seniority: intern.
Applications are handled by NVIDIA. Apply on NVIDIA

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorchTensorFlowJAX

Questions you could be asked

What's a project where you used PyTorch hands-on?
Walk me through how you've used TensorFlow in your day-to-day work.
What are the limits of JAX that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: PyTorch, TensorFlow, and JAX. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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