Senior AI Infrastructure Engineer for Robotics Foundation Models

Socket.dev; Santa Clara (CA); On-site; USD 224,000 - 356,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a senior/principal engineer to build and optimize infrastructure for large-scale foundation model training in the GEAR group. You will lead distributed training across multi-modal data and robotics workloads, collaborating with researchers to deploy scalable pipelines.

The role emphasizes CUDA, PyTorch/TensorFlow/JAX, Kubernetes, and high-performance C++. Equity and benefits accompany a competitive base salary. Applications open until 2026-01-13.

Qualifications

• Bachelor's degree in CS/Robotics/Engineering or 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 PyTorch, JAX, or TensorFlow.
• Deep understanding of GPU acceleration, CUDA, and cluster tools like Kubernetes.
• Strong Python and a high-performance language such as C++ for efficient system development.
• Experience with large-scale GPU clusters and job scheduling tools (e.g., SLURM, Kubernetes).

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 for multimodal datasets including videos, text, and sensors.
• Develop robust monitoring and debugging tools for training workflows on large GPU clusters.
• Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines.

Skills

Python programming

Distributed training

GPU acceleration

CUDA programming

Kubernetes

MLOps

Education

Bachelor's degree in Computer Science/Robotics/Engineering

Master’s or PhD in CS/Robotics/Engineering

Tools

PyTorch

JAX

TensorFlow

Job description

NVIDIA is seeking a senior/principal engineer to build and optimize infrastructure for large-scale foundation model training in the GEAR group. You will lead distributed training across multi-modal data and robotics workloads, collaborating with researchers to deploy scalable pipelines.

The role emphasizes CUDA, PyTorch/TensorFlow/JAX, Kubernetes, and high-performance C++. Equity and benefits accompany a competitive base salary. Applications open until 2026-01-13.