NVIDIA
Senior Research Engineer, Foundation Model Training Infrastructure
$224K–$356K
US, CA, Santa Clara · Senior · Full-time · Posted Jan 9, 2026
- Experience
- 10+ years of full-time industry experience in large-scale MLOps and AI infrastructure.
- Education
- Bachelor's degree in Computer Science, Robotics, Engineering, or a related field.
About the job
Build and maintain distributed training infrastructure for multimodal foundation models used in robotics research.
What you'll do
- Design distributed training systems and improve GPU and cluster utilization.
- Build scalable data-loading, preprocessing, monitoring, and debugging tools for multimodal training workflows.
- Collaborate with researchers to integrate model architectures into scalable training pipelines.
What they ask for
- Bachelor's degree in Computer Science, Robotics, Engineering, or a related field.
- Proven experience designing and optimizing distributed training systems.
- Deep understanding of GPU acceleration, CUDA programming, and cluster management.
- Strong Python and C++ programming skills, with experience in large-scale GPU clusters, HPC, and job scheduling or orchestration tools.
Nice to have
- Master’s or PhD’s degree in a related field; Tech Lead experience; large-scale LLM and multimodal LLM training infrastructure experience.
- Open-source AI framework contributions or publications at top-tier AI conferences.
Pay
224,000 USD - 356,500 USD (base salary)
Tools
PyTorch, JAX, TensorFlow, CUDA, Kubernetes, Python, C++, SLURM
AI focus
Infrastructure for large-scale multimodal foundation-model training, including models for robotics and embodied AI.
Model-written summary · the original posting is authoritative