Senior Research Engineer, Foundation Model Training Infrastructure
$224k - $357k • Remote • US, CA, Santa Clara
Posted 1d ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a senior or principal engineer to build cutting-edge infrastructure for large-scale foundation model training within the Generalist Embodied Agent Research (GEAR) group. This team is spearheading Project GR00T, an initiative focused on developing foundation models and full-stack technology for humanoid robots. You will collaborate with a research team known for influential work in multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation, contributing to impactful research projects and product roadmaps.
Responsibilities
- Design and maintain large-scale distributed training systems for multi-modal foundation models in robotics.
- Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets.
- Implement scalable data loaders and preprocessors for multimodal datasets (videos, text, sensor data).
- Develop robust monitoring and debugging tools for training workflows on large GPU clusters.
- Collaborate with researchers to integrate advanced 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 using frameworks like PyTorch, JAX, or TensorFlow.
- Deep understanding of GPU acceleration, CUDA programming, and cluster management tools (e.g., Kubernetes).
- Strong programming skills in Python and a high-performance language like C++.
- Extensive experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM, Kubernetes).
Benefits
- Equity
- Benefits