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 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.

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 the 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 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!