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# Senior Deep Learning Performance Architect

- **Company:** NVIDIA Corporation
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $152,000.0 - $241,500.0
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Test Suite, C++ (Programming Language), Profiling, Computer Engineering, General-Purpose Computing on Graphics Processing Units, Python (Programming Language), Machine Learning, High Performance Computing, Deep Learning, Parallel Computation, Information Technology, Data Analytics, Programming Languages
- **Published:** August 28, 2026
- **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Deep-Learning-Performance-Architect_JR2020181-1

## About the Role

* Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.
 * 4+ years of relevant work or research experience.
 * A strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture.
 * A strong background in high performance power efficient designs, energy efficient high performance computing, performance analysis and profiling to identify performance bottlenecks.
 * Fluency in programming languages such as Python, C, C++.
 * Experience and familiarity with GPU computing and parallel programming models.
 * You have firsthand work experience with analytical performance modeling, profiling, and analysis.

## Description

* As a member of our deep learning architecture team, you will craft high performance energy efficient system and processor architectures to extend the state of the art in deep learning.
 * Prototype key deep learning and data analytics algorithms and applications.
 * Analyze trade-offs in performance, cost and power developing analytical models, simulators and test suites.
 * Analyze architecture performance and/or energy efficiency considering deep learning workloads, modeling and prototyping.
 * Collaborate across the company to guide the direction of machine learning, working with software, research and product teams.


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