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# Senior Software Engineer, AI Performance Analysis

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $168,000.0 - $270,250.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Computer Engineering, Programming Tools, Python (Programming Language), Open Source Technology, Performance Tuning, Software Engineering, Delivery Pipeline, Build Management, Information Technology
- **Published:** July 2, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p1d1xl3zw0

## About the Role

* 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

## Description

* 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.


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