Senior Researcher - GPU Performance | Microsoft Careers

Microsoft

Quick summary

Work type: On-site
Location: WA
Salary: $119,800–$234,700 / yr
Posted: 128 days ago
Closes: Jul 26, 2026

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Competitive pay

How this pay compares to similar roles

Similar $199k

This role $177k

$105k most similar roles pay here $256k

This role pays less than 60% of similar roles. Most pay $162,000–$235,750 — the shaded band above. At the midpoint, this role pays about $177k versus about $199k for comparable roles.

Based on 240 similar postings.

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About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 571 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 522 roles with salary data.

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At a glance

TL;DR · Senior Researcher - GPU Performance | Microsoft Careers

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As a Senior Researcher in GPU Performance for Microsoft’s Systems Innovation initiative, you will join an Applied Research team focused on advancing efficiency across AI systems. Your primary responsibilities include designing and implementing optimized GPU kernels for complex computational workloads such as AI inferencing, developing novel optimization techniques, profiling kernel performance with advanced diagnostic tools, and contributing to the development of internal GPU computing frameworks. You will collaborate closely with other researchers to enhance model performance and document your strategies effectively. The ideal candidate has a strong background in GPU architecture, machine learning, and systems research, along with reliable C++ programming skills and experience using CUDA, ROCm, Triton, PTX, or similar frameworks. This role involves tackling challenging technical problems at scale within Microsoft’s expansive collaboration and productivity platform, impacting hundreds of millions of users globally.

Skills

CUDA ROCm Triton PTX CUTLASS PyTorch TensorFlow C++ GPU Parallel Computing Algorithm Optimization Performance Profiling Automated Code Generation Compiler Optimization CI/CD

What you'll do

Design and implement GPU kernels for complex AI inferencing workloads.
Develop novel optimization techniques for generating efficient GPU kernels.
Profile and analyze kernel performance using advanced diagnostic tools.
Generate automated solutions to optimize and tune GPU kernels.
Document optimization strategies and maintain performance benchmarks.
Collaborate with researchers to enhance model performance in production systems.

What we're looking for

Doctorate in relevant field or equivalent experience.
2+ years of experience in GPU architecture and parallel computing optimization.
Proficient in GPU programming with performance profiling tools.
Strong C++ programming skills.
Expert knowledge in CUDA, ROCm, Triton, PTX, CUTLASS, or similar frameworks.
Experience with machine learning frameworks like PyTorch or TensorFlow.
Publication record in top-tier conferences or journals.

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