PhD Research Intern, Generalist Embodied Agents Research

NVIDIA

. Design and implement novel AI algorithms and models for general-purpose humanoid robots and embodied agents .

Posted 9/17/2026full-timeRemote • California • United StatesEntry Level💰 $38 - $94 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI algorithms for humanoid robots, with strong capabilities in large-scale AI training and inference methods. Proficient in Python and experienced with multimodal foundation models, robotics, and control methods.

Highest-signal resume keywords

PhD In Computer Science/EngineeringRapid PrototypingModel Training FrameworksLarge-Scale Machine Learning SystemsRobot Kinematics And Dynamics

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Algorithm DesignModel TrainingPython ProgrammingC++ ProficiencyCUDA ProficiencyMultimodal Foundation ModelsRobot LearningControl MethodsPhysics Simulation FrameworksHands-On Training Experience

Tools & Technologies

PyTorchJaxTensorFlowMujocoIsaac Suite

Industry Keywords

AI ModelsHumanoid RobotsEmbodied AgentsLarge-Scale AI TrainingInference Methods

Tech Stack

Tools & technologies

PythonPyTorchTensorflowC++

About the role

Key responsibilities & impact

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 NVIDIA to transfer research to products and services

Requirements

What you’ll need

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 multimodal foundation models or robotics
Hands-on training experience and publications in LLMs, vision-language models, video generative models, diffusion models, or action-based transformers, or in robot learning
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, and whole body control
Familiarity with physics simulation frameworks such as Mujoco and Isaac suite

Benefits

Comp & perks

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