AI Performance Tools Engineer — Equity Eligible

NVIDIA Corporation; Hillsboro (OR); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a Senior roles-focused candidate to design and build performance analysis tools for AI training and inference workloads. The role emphasizes translating engineer needs into scalable tooling and developing integrations between profiling infra and AI frameworks.

You will collaborate with performance engineers, hardware architects, and software teams to ensure profiling aligns with real-world AI workloads and identify bottlenecks with automated detection approaches.

Qualifications

• MS or PhD in CS/CE or related field, or equivalent experience.
• 6+ years of relevant work experience.
• Deep knowledge of AI workloads and performance characteristics.
• Experience building tools/workflows/infrastructure used by other engineers.
• Strong Python and C++ development skills.
• Ability to translate user requirements into scalable tooling.
• Up to date with AI-enabled tooling for software development and performance analysis.
• Strong interpersonal skills to collaborate across teams.

Responsibilities

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

Skills

Python

C++

AI workload knowledge

Tooling development

Education

MS/PhD in Computer Science or Computer Engineering or related field

Tools

Profiling tools

Developer tooling experience

Job description

NVIDIA Corporation is seeking a Senior roles-focused candidate to design and build performance analysis tools for AI training and inference workloads. The role emphasizes translating engineer needs into scalable tooling and developing integrations between profiling infra and AI frameworks.

You will collaborate with performance engineers, hardware architects, and software teams to ensure profiling aligns with real-world AI workloads and identify bottlenecks with automated detection approaches.