Senior Research Engineer, Foundation Model Training Infrastructure

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 to build foundation models and full-stack technology for humanoid robots.

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

Responsibilities

• 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 reliability and performance of training workflows on large GPU clusters.
• Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines.

Requirements

• 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 such as 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

• Master's or PhD degree in Computer Science, Robotics, Engineering, or related field.
• Demonstrated Tech Lead experience, coordinating engineering teams and driving projects from conception to deployment.
• Strong experience 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. Join us to be at the forefront of developing general-purpose robots and large-scale foundation models!

Compensation and Benefits

The base salary range is $224,000 - $356,500 USD per year. Salary is determined based on location, experience, and peer pay. Additional eligibility for equity and benefits is provided.