Senior AI Infra Architect for Multi-GPU Training + Equity

NVIDIA Gruppe; California (MO); On-site; USD 224,000 - 431,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA seeks a Deep Learning Software Infrastructure Engineer to advance autonomous vehicles by building scalable training libraries and infrastructure for multi-thousand GPU clusters. You will enable end-to-end training on massive datasets and collaborate with researchers and platform teams to improve efficiency and safety.

Role involves owning core infrastructure components, optimizing data loaders and scheduling, and scaling systems with growing GPU capacity.

Qualifications

• 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 preferred), large‑scale training (DDP/FSDP, NCCL), 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

Collaboration

Education

BS/MS/PhD in CS/EE

Tools

PyTorch

Kubernetes

Slurm

Lustre

NCCL

RoCE

Job description

NVIDIA seeks a Deep Learning Software Infrastructure Engineer to advance autonomous vehicles by building scalable training libraries and infrastructure for multi-thousand GPU clusters. You will enable end-to-end training on massive datasets and collaborate with researchers and platform teams to improve efficiency and safety.

Role involves owning core infrastructure components, optimizing data loaders and scheduling, and scaling systems with growing GPU capacity.