Nvidia PhD Research Intern Generalist Embodied Agents - Fall 

United States, Texas 

753027475

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

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 compute 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.

You will also be eligible for Intern