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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 .
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