Senior Research Engineer, Foundation Model Training Infrastructure
NVIDIA· Engineer, Sys SW
Santa Clara, CA$224k - $356.5kfull-timePosted 7mo ago
About the role
Senior/principal engineer in the GEAR group building infrastructure for large-scale foundation model training for robotics, multimodal models, and embodied AI. Focus on distributed training systems, data pipelines, and scalable tooling for large GPU clusters.
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.
Qualifications
- 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)
Skills
Required:Distributed training systemsMultimodal data pipelinesGPU acceleration and CUDACluster managementProgramming languages
Benefits
- equity
- benefits (per NVIDIA benefits)
Last updated Jul 3, 2026. Interested? Apply on the company site.
About NVIDIA
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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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