Senior Research Engineer, Foundation Model Training Infrastructure

5 Months ago • 10 Years + • Devops • $224,000 PA - $356,500 PA

Job Summary

Job Description

NVIDIA's GEAR group seeks a Senior Research Engineer to design and maintain large-scale distributed training systems for multi-modal foundation models in robotics. This role involves optimizing GPU and cluster utilization, implementing scalable data loaders, developing monitoring tools, and collaborating with researchers. The successful candidate will have 10+ years of experience in large-scale MLOps and AI infrastructure, expertise in PyTorch/JAX/TensorFlow, CUDA programming, and cluster management tools like Kubernetes. The work contributes directly to NVIDIA's Project GR00T, a moonshot initiative in humanoid robot technology.
Must have:
  • 10+ years MLOps/AI infrastructure experience
  • Distributed training system design (PyTorch/JAX/TensorFlow)
  • GPU acceleration, CUDA, Kubernetes expertise
  • Python & C++ programming skills
  • Large-scale GPU cluster experience
Good to have:
  • Master's/PhD in CS/Robotics/Engineering
  • Tech Lead experience
  • LLM/multimodal LLM infrastructure experience
  • Open-source contributions or publications
Perks:
  • Equity
  • Benefits

Job Details

NVIDIA is searching for a senior or principal engineer who specializes in building cutting-edge infrastructure for large-scale foundation model training in the Generalist Embodied Agent Research (GEAR) group. Our team is leading Project GR00T, NVIDIA’s moonshot initiative at building foundation models and full-stack technology for humanoid robots.

You will work with an amazing and collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and more. Your contributions will have a significant impact on our research projects and product roadmaps.

What you will be doing:

  • Design and maintain large-scale distributed training systems to support multi-modal foundation models for robotics.

  • Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets.

  • Implement scalable data loaders and preprocessors tailored for multimodal datasets, including videos, text, and sensor data.

  • Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows on large GPU clusters.

  • Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines.

What we need to see:

  • Bachelor's degree in Computer Science, Robotics, Engineering, or a related field;

  • 10+ years of full-time industry experience in large-scale MLOps and AI infrastructure;

  • Proven experience designing and optimizing distributed training systems with frameworks like PyTorch, JAX, or TensorFlow.

  • Deep understanding of GPU acceleration, CUDA programming, and cluster management tools like Kubernetes.

  • Strong programming skills in Python and a high-performance language such as C++ for efficient system development.

  • Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM, Kubernetes).

Ways to stand out from the crowd:

  • Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field;

  • Demonstrated Tech Lead experience, coordinating a team of engineers and driving projects from conception to deployment;

  • Strong experience at building large-scale LLM and multimodal LLM training infrastructure;

  • Contributions to popular open-source AI frameworks or research publications in top-tier AI conferences, such as NeurIPS, ICRA, ICLR, CoRL.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and productive people in the world. Please join us and be part of the forefront of developing general-purpose robots and large-scale foundation models!

The base salary range is 224,000 USD - 356,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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