# Deep Learning Software Infrastructure Engineer

**Company**: NVIDIA
**Location**: Santa Clara, CA
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Deep-Learning-Software-Infrastructure-Engineer_JR2027872?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/deep-learning-software-infrastructure-engineer-8b5d4fbb-749/

## Description

NVIDIA is seeking a Deep Learning Software Infrastructure Engineer to propel its Autonomous Vehicles project forward.

In this role, you will build and scale training libraries and infrastructure that make end-to-end autonomous driving models possible.

**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.

**Requirements**

- 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.

**Nice to Have**

- Shown experience scaling large GPU training clusters with >1,000 GPUs.

- Expertise in fault resilience and high availability, including elastic training and large-scale observability.

- Tried leadership skills as a hands-on technical authority, encouraging others and establishing guidelines for ML systems engineering.

You will also be eligible for equity and benefits.

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## Skills

### Required
- Python
- PyTorch
- deep learning
- distributed systems
- performance profiling
- datacenter networking
- parallel filesystems
- storage systems
- schedulers

### Nice to have
- fault resilience
- high availability
- elastic training
- large-scale observability
- leadership skills

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Deep-Learning-Software-Infrastructure-Engineer_JR2027872?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)