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Nvidia Senior Research Scientist Multimodal Foundation Models Robotics 
United States, California 
249830023

Yesterday
US, CA, Santa Clara
time type
Full time
posted on
Posted 6 Days Ago
job requisition id

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:

  • A Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience.

  • 5 years of relevant work/research experience across one or both of these fields:

    • Multimodal Foundation Models

      • Hands-on training experience and publications in at least one of the following topics:LLMs; Large vision-language models; Video generative models and diffusion algorithms; or Action-based transformers.

      • Outstanding engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow, etc.). Python is required; C++ and CUDA proficiencies are a big plus;

      • Excellent skills in working with large-scale machine learning/AI systems and compute infrastructure.

    • Robotics:

      • Hands-on training experience and publications in robot learning, such as reinforcement learning, imitation learning, classical control methods, etc.

      • Strong programming skills in Python, C++, ROS, and machine learning frameworks like PyTorch.

      • Deep understanding of robot kinematics, dynamics, and sensors;

      • Ability to safely operate robot hardware, lab equipment, and tools;

      • Knowledge of control methods, including PID, model predictive control, and whole-body control;

      • Familiarity with physics simulation frameworks such as MuJoCo and Isaac Sim;

      • Robot hardware design and hands-on building experience.

You will also be eligible for equity and .