1 day ago
Durham, NC, USA +4 moreMid Level
H1B sponsor
Base Salary
$124k - $196k/yr
Responsibilities
- Propose and implement reliable, secure, and performance-optimized solutions for GPU clusters supporting internal AI researchers.
- Design, develop, and maintain systems for validating, monitoring, and operating GPU clusters at scale.
- Reduce operational disruption and toil through self-service reliability, operational excellence, AIOps, and Agentic AI solutions.
- Collaborate across the AI Platform organization to identify and systematically solve infrastructure pain points.
- Participate in on-call support for systems and platforms owned by the team.
Requirements
- Bachelor's or master's degree in Computer Science, Engineering, or equivalent experience.
- At least 2 years of software or platform engineering experience, including at least 1 year in ML infrastructure or distributed systems.
- Experience with software development on Linux-based platforms.
- Strong coding skills in Python, C++, or Rust.
- Experience with Docker, Kubernetes, GitLab CI, and automated deployments.
- Experience applying AIOps or Agentic AI successfully in production.
- Preferred experience with full-stack development, relational data modeling, database optimization, JavaScript, CSS, and API services.
- Preferred experience running Slurm or custom scheduling frameworks in production ML environments.
- Familiarity with GPU computing, Linux systems internals, and performance tuning at scale.
Benefits
- Eligible for equity and benefits.
Tech Stack
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.