Principal AI and ML Infra Software Engineer, GPU Clusters

Nvidia

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Santa Clara, CARedmond, WA
Salary: $272,000–$431,250 / yr
Employment: Full-time
Posted: 13 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k

This role $352k

$136k $463k

below market most similar roles pay here above market

This role pays more than 99% of similar roles. Most pay $196,750–$254,750 — the blue band above. At the midpoint, this role pays about $352k versus about $226k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Principal AI and ML Infra Software Engineer, GPU Clusters

Role Posting Log in to save

The Principal AI and ML Infra Software Engineer, GPU Clusters joins the Hardware Infrastructure team to enhance researcher efficiency by implementing improvements throughout the entire stack. This role involves collaborating with customers to identify infrastructure deficiencies and converting research insights into actionable improvements. Key responsibilities include driving long-term roadmaps, monitoring performance for high availability, and optimizing resource utilization. The engineer will work with researchers, data engineers, and DevOps professionals to develop a cohesive ecosystem. Required expertise includes High Performance Computing, accelerated computing like GPUs, and storage systems such as Lustre or GPFS. Candidates must possess skills in Slurm, Kubernetes, Infiniband, and Docker. Technical proficiency in Python, Go, and Bash is required to manage distributed training operations using PyTorch, NeMo, or JAX across cloud platforms.

Skills

AI/ML HPC GPU PyTorch JAX Kubernetes Slurm Docker Python Go Bash Lustre GPFS BeeGFS Infiniband RoCE AWS GCP Azure NeMo Distributed Training Parallel Computing

What you'll do

Convert research team requirements into actionable infrastructure improvements.
Identify and lead initiatives to resolve researcher efficiency bottlenecks.
Drive the long-term roadmap for AI and ML infrastructure initiatives.
Monitor and optimize infrastructure for high availability, scalability, and resource utilization.
Define and improve measurable metrics for AI researcher efficiency.
Develop a cohesive AI/ML infrastructure ecosystem with data engineers and DevOps.
Integrate the latest AI/ML technologies and frameworks into the organization.

What we're looking for

BS or similar background in Computer Science or related area, or equivalent experience.
15+ years of demonstrated expertise in AI/ML and HPC tasks and systems.
Hands-on experience operating HPC grade infrastructure and in-depth knowledge of accelerated computing, storage, scheduling, and high-speed networking.
Experience with container technologies such as Docker and Enroot.
Capability in supervising and improving substantial distributed training operations using PyTorch, NeMo, or JAX.
In-depth understanding of AI/ML workflows involving data processing, model training, and inference pipelines.
Proficiency in programming and scripting languages such as Python, Go, and Bash.
Familiarity with cloud computing platforms and experience with parallel computing frameworks and paradigms.

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