Senior DL Infra Engineer - Multi-GPU AI Training

2100 NVIDIA USA; California (MO); On-site; USD 272,000 - 431,000; Full time

Job summary

NVIDIA is seeking a Deep Learning Software Infrastructure Engineer to advance its autonomous vehicles projects. You will design and scale training libraries for multi-thousand GPU clusters, improving data loading, distributed training, and fault-resilient pipelines.

You'll work with ML researchers, infra engineers, and platform teams to deliver robust systems that scale with GPU capacity and dataset size, while maintaining developer efficiency and speed.

Qualifications

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.
• 12+ years of professional experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-scale data infrastructure.
• Extensive knowledge in deep learning frameworks (PyTorch is preferred), large scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.
• Strong systems background: datacenter networking (RoCE, IB), parallel filesystems (Lustre), storage systems, schedulers (Slurm, Kubernetes, etc.).
• Proficiency in Python with experience writing production-grade libraries, orchestration layers, and automation tools.
• Ability to work closely with multi-functional teams (ML researchers, infra engineers, product leads) and translate requirements into robust systems.

Responsibilities

• Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
• Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
• Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.
• Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
• Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.
• Partnering with leadership to ensure infrastructure scales with growing GPU capacity and dataset size while maintaining developer efficiency and stability.

Skills

Python

Distributed systems

Deep learning

Performance profiling

Team collaboration

Education

BS/MS/PhD in CS/EE or related

Tools

PyTorch

NCCL

Slurm

Kubernetes

Lustre

RoCE

IB

Job description

NVIDIA is seeking a Deep Learning Software Infrastructure Engineer to advance its autonomous vehicles projects. You will design and scale training libraries for multi-thousand GPU clusters, improving data loading, distributed training, and fault-resilient pipelines.

You'll work with ML researchers, infra engineers, and platform teams to deliver robust systems that scale with GPU capacity and dataset size, while maintaining developer efficiency and speed.