Senior AI Performance Tools Engineer

NVIDIA Corporation; Santa Clara (CA); Vor Ort; USD 184.000 - 288.000; Vollzeit

Benefits dieser Stelle

Equity

Benefits package

Zusammenfassung

NVIDIA Corporation is seeking a senior software engineer to automate and optimize performance analysis workflows for AI training and inference workloads. You will design and build scalable tools and workflows that empower a broad audience of engineers across the company.

Responsibilities include translating user needs into tooling, integrating profiling with AI frameworks, and collaborating with performance engineers and hardware teams to identify bottlenecks and automate diagnostics.

Qualifikationen

• MS/PhD in Computer Science, Computer Engineering, or related field (or equivalent experience).
• 6+ years of relevant work experience; deep knowledge of AI workloads and performance characteristics.
• Experience building tools, workflows, or infrastructure used by other engineers.
• Strong software development skills (Python, C++ preferred).
• Ability to translate user requirements into scalable tooling solutions.

Aufgaben

• Design and build performance analysis tools and workflows for AI training and inference workloads.
• Understand engineers' needs and translate them into scalable tooling.
• Develop integrations between profiling infrastructure and AI frameworks/workflows.
• Collaborate with performance engineers, hardware architects, and software teams to align profiling with real-world workloads.
• Identify performance bottlenecks and develop automated detection/diagnosis approaches.

Kenntnisse

Python

C++

Tooling development

AI workloads

Translate requirements into tooling

Ausbildung

MS/PhD in Computer Science or Computer Engineering

6+ years of relevant experience

Tools

Profiling frameworks

Jobbeschreibung

NVIDIA Corporation is seeking a senior software engineer to automate and optimize performance analysis workflows for AI training and inference workloads. You will design and build scalable tools and workflows that empower a broad audience of engineers across the company.

Responsibilities include translating user needs into tooling, integrating profiling with AI frameworks, and collaborating with performance engineers and hardware teams to identify bottlenecks and automate diagnostics.