Senior Research Scientist, Multimodal Foundation Models and Robotics

Nvidia

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$192,000–$304,750 / yr
Posted
45 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $217k
This role $248k
$156k most similar roles pay here $321k

This role pays more than 79% of similar roles. Most pay $185,250–$248,375 — the shaded band above. At the midpoint, this role pays about $248k versus about $217k for comparable roles.

Based on 239 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 994 open roles on FindRole.

Listed pay typically runs $168,000–$270,250 across 977 roles with salary data.

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At a glance

TL;DR · Senior Research Scientist, Multimodal Foundation Models and Robotics

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As a Senior Research Scientist in NVIDIA’s Generalist Embodied Agent Research (GEAR) group, you will contribute to groundbreaking projects like Project GR00T, focusing on multimodal foundation models for humanoid robots. Your daily tasks include designing AI algorithms and large-scale training methods, optimizing models for both simulation and real-world deployment, and collaborating with cross-functional teams to translate research into practical applications. Ideal candidates hold a Ph.D. in Computer Science or related fields and have extensive experience in either multimodal foundation models—requiring expertise in frameworks like PyTorch and proficiency in Python—or robotics, involving hands-on skills in robot learning, control methods, and hardware design. This role demands deep knowledge of large-scale machine learning systems and the ability to work with complex AI infrastructure, making it a pivotal position in advancing autonomous technology at NVIDIA.

Skills

Python PyTorch Jax Tensorflow C++ CUDA ROS MuJoCo Isaac Sim Reinforcement Learning Imitation Learning PID Control MPC Whole-Body Control Robot Kinematics Robot Dynamics Sensor Integration

What you'll do

  • Design and implement novel AI algorithms for general-purpose humanoid robots.
  • Develop large-scale training methods for multimodal foundation models.
  • Optimize AI models for deployment in physical simulation environments.
  • Deploy AI systems on robot hardware for real-world applications.
  • Collaborate with cross-functional teams to integrate research into products.

What we're looking for

  • Ph.D. in Computer Science/Engineering or equivalent research experience.
  • 5 years of relevant work/research experience in multimodal foundation models.
  • Hands-on training experience and publications in LLMs, vision-language models, video generative models, or action-based transformers.
  • Proficiency in Python with strong skills in PyTorch, Jax, Tensorflow; C++ and CUDA are beneficial.
  • Experience developing large-scale AI systems and optimizing for compute infrastructure.
  • Strong background in robotics including robot learning, control methods, and hardware design.

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