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# Software Engineer - AI Research Clusters

- **Company:** NVIDIA Ltd.
- **Location:** Austin, TX, United States
- **Salary:** $124,000.0 - $195,500.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Cascading Style Sheets (CSS), Computer Clusters, Relational Databases, Linux, Distributed Systems, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Performance Tuning, Software Deployment, Software Engineering, AI Platforms, Gitlab-ci, Kubernetes, Information Technology, Deployment Automation, Slurm, Machine Learning Operations, Virtual Agents, Software Coding, Restful APIs, Docker
- **Published:** May 15, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=8c6d4332c5083a84

## About the Role

Do you have experience in Software deployment?, Do you have a Bachelor's degree?, * BS/MS in Computer Science, Engineering, or equivalent experience.

 * 2+ years in software/platform engineering, including 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, automated deployments.
 * Experience with AIOps or Agentic AI and apply it successfully in production environment.

Ways To Stand Out From The Crowd:

 * Proficiency with full-stack development: Relational Data Modeling, DB optimization, REST API Semantics, Javascript, CSS, providing API as a service.
 * Passion for building developer-centric platforms with great UX and strong operational reliability.
 * Experience running Slurm or custom scheduling frameworks in production ML environments.
 * Familiarity with GPU computing, Linux systems internals, and performance tuning at scale.

## Description

* In this position, you will work with coworkers across the AI Platform organization to understand the pain points of validating, monitoring and operating GPU clusters at scale. Then you will design, develop and maintain engineering solutions to solve those pain points systematically.
 * You will also research in traditional AIOps and the emerging Agentic AI, and leverage it to further reduce the operation toil.
 * You will participate in on-call support for systems, platforms built and owned by the team.


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