Software Engineer, AI Research Clusters

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAWestford, MAAustin, TXHillsboro, ORDurham, NC
Employment: Full-time
Posted: 52 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $201k

$139k $252k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $166,125–$235,750.

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 1675 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1080 roles with salary data.

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At a glance

TL;DR · Software Engineer, AI Research Clusters

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As a Software Engineer - AI Research Clusters, you will join the AI Platform organization to design, develop, and maintain engineering solutions for functional, reliable, and performance-optimal GPU clusters. You will work to reduce operational disruption for internal researchers by solving pain points related to validating, monitoring, and operating these clusters at scale. Your daily work involves implementing systems that empower scientists to train and deploy advanced machine learning models. You will utilize Python, C++, or Rust within Linux-based platforms, leveraging tools like Docker, Kubernetes, and GitLab CI for automated deployments. The role requires applying AIOps and Agentic AI to reduce operational toil. You will also handle on-call support for these platforms, focusing on distributed systems, ML infrastructure, and performance tuning for large-scale GPU computing environments.

What does a Software Engineer earn in California?

Median $214500 from 1157 postings across 75 companies.

See salary data

Skills

Python C++ Rust Kubernetes Docker GitLab CI Linux AIOps Agentic AI Slurm REST API Relational Data Modeling Javascript CSS Distributed Systems ML Infrastructure

What you'll do

Design and maintain engineering solutions to validate, monitor, and operate GPU clusters at scale.
Implement solutions to ensure GPU clusters are functional, reliable, secure, and performance-optimal.
Reduce operational disruption and overhead for internal researchers training and developing ML models.
Research and leverage AIOps and Agentic AI to reduce operational toil.
Provide on-call support for systems and platforms owned by the team.
Develop tools to empower researchers for self-service continuous improvement on reliability and performance.

What we're looking for

BS/MS in Computer Science, Engineering, or equivalent experience.
2+ years in software/platform engineering.
1 year in ML infrastructure or distributed systems.
Experience in software development lifecycle on Linux-based platforms.
Strong coding skills in languages such as Python, C++, or Rust.
Experience with Docker, Kubernetes, GitLab CI, and automated deployments.
Experience with AIOps or Agentic AI applied successfully in production environments.
Proficiency with full-stack development, relational data modeling, and REST API semantics (preferred).

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