NVIDIA
Artificial Intelligence
SoftwareEngineer-AIResearchClusters
Neural analysis suggests this role is
optimal for Mid candidates.
“Software Engineer - AI Research Clusters at NVIDIA. Skills: AI Research Clusters, GPU clusters, machine learning innovation, AIOps, Agentic AI, Python, C++, Rust, Docker, Kubernetes. Propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters. Reduce operational disruption and overhead for internal researchers”
What You'll Achieve.
ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters; enable them to focus on training and development by reducing operational disruption and overhead; empower them for self-service continuous improvement on reliability, operational excellence & performance; empower scientists and engineers to train, fine-tune, and deploy the most advanced ML models on some of the world’s most powerful GPU systems; reduce the operation toil
Industry & Context.
understand the pain points of validating, monitoring and operating GPU clusters at scale; design, develop and maintain engineering solutions to solve those pain points systematically
Participate in on-call support for systems, platforms built and owned by the team
What They're Looking For.
Must Have
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, 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
Nice to Have
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 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
What You'll Do.
Propose and implement engineering solutions to ensure delivery of functional
and performance-optimal GPU clusters
Reduce operational disruption and overhead for internal researchers
Empower researchers for self-service continuous improvement on reliability
operational excellence & performance
develop and maintain engineering solutions to solve pain points of validating
monitoring and operating GPU clusters at scale
Research in traditional AIOps and the emerging Agentic AI
and leverage it to further reduce operation toil
How You'll Work.
Team & Collaboration
Work with coworkers across the AI Platform organization
Full Job Description
NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention—the GPU—functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a Software Engineer to help accelerate the next era of machine learning innovation. In this role, you will propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters to internal researchers, enable them to focus on training and development by reducing operational disruption and overhead, empower them for self-service continuous improvement on reliability, operational excellence & performance. Your work will empower scientists and engineers to train, fine-tune, and deploy the most advanced ML models on some of the world’s most powerful GPU systems. **What You 'll Be Doing:** * 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. **What We Need To See:** * 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 Crow
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