NVIDIA

AI workload optimization

SeniorSoftwareEngineer,AIPerformanceAnalysis

$168–322k Santa Clara, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Software Engineer, AI Performance Analysis at NVIDIA. Skills: AI performance analysis, tool development, workflow automation. 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”

What You'll Achieve.

automate and optimize performance analysis workflows for AI training and inference workloads; push these boundaries even further

Industry & Context.

AI workload optimization
Problems you'll solve

Identify performance bottlenecks; develop automated approaches to detect and diagnose them

What They're Looking For.

Must Have

M. S. , or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience), 6+ years of relevant work experience, Deep knowledge of AI workloads, frameworks, and performance characteristics, Experience building tools, workflows, or infrastructure used by other engineers, software development skills (Python, C++ preferred), Ability to translate user requirements into scalable tooling solutions, Up to date with AI-enabled tooling for software development and performance analysis, interpersonal skills for understanding engineer difficulties and working across multi-functional teams

Nice to Have

Experience profiling or optimizing AI training or inference pipelines at scale, Background building developer tools or platforms for ML engineers, Contributions to open-source AI tooling or frameworks

What You'll Do.

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

Develop integrations between profiling infrastructure and AI frameworks and workflows

Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them

How You'll Work.

Team & Collaboration

Collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads; working across multi-functional teams

Full Job Description

NVIDIA GPU Architecture Group is seeking a senior software engineer to automate and optimize performance analysis workflows for AI training and inference workloads. You will not only perform analysis but also reshape how it's done, building tools and workflows that scale across a broad audience of engineers. NVIDIA is a world-class leader in AI workload optimization, and your work will push these boundaries even further! **What you 'll be doing:** * 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 ensure profiling capabilities align with real-world AI workloads. * Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them. **What we need to see:** * M.S., or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience). 6+ years of relevant work experience * Deep knowledge of AI workloads, frameworks, 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. * Up to date with AI-enabled tooling for software development and performance analysis. * Strong interpersonal skills for understanding engineer difficulties and working across multi-functional teams. **Ways to stand out from the crowd:** * Experience profiling or optimizing AI training or inference pipelines at scale * Background building developer tools or platforms for ML engineers * Contributions to open-source AI tooling or frameworks Your base salary will be determined based on your location, experience, and th

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