Senior Software Engineer - Performance Tooling | Microsoft Careers

Microsoft

Quick summary

Work type
On-site
Location
US
Salary
$119,800–$234,700 / yr
Posted
2 days ago
Closes
Nov 30, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $182k
This role $177k
$106k most similar roles pay here $248k

This role pays more than 66% of similar roles. Most pay $152,955–$211,181 — the shaded band above. At the midpoint, this role pays about $177k versus about $182k for comparable roles.

Based on 240 similar postings.

Employer

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 728 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 664 roles with salary data.

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At a glance

TL;DR · Senior Software Engineer - Performance Tooling | Microsoft Careers

As a Senior Software Engineer - Performance Tooling on Microsoft’s AI Frameworks team, you will work across multiple layers of the AI software stack, including abstractions, programming models, compilers, runtimes, libraries, and APIs, to enable large-scale model training and inference. Your day-to-day responsibilities include benchmarking OpenAI and other LLMs for performance on GPUs and Microsoft hardware, debugging and optimizing performance for training/inference workloads on CPUs/GPUs, monitoring performance regressions, and driving continuous improvements to reduce time-to-deploy and hardware footprint. You will leverage C++, Python, PyTorch, TensorFlow, ONNX Runtime, CUDA, ROCm, and Triton in a high-performance computing environment, collaborating closely with researchers and engineers to deliver scalable, production-ready AI solutions for major Microsoft products like Office, Windows, Bing, SQL Server, and Dynamics.

What you'll do

  • Benchmark OpenAI and other LLM models for performance on GPUs and Microsoft hardware.
  • Debug and optimize training/inference workloads on CPUs/GPUs for improved efficiency.
  • Monitor performance regressions and drive continuous improvements in deployment time and hardware usage.
  • Develop scalable, production-ready AI performance enhancements across the software stack.
  • Profile state-of-the-art LLMs using GPU profiling tools to ensure optimal performance.

What we're looking for

  • 6+ years of technical engineering experience with coding in C++ or Python.
  • Bachelor's Degree in Computer Science or related field plus extensive relevant work experience.
  • 4+ years’ hands-on experience working on high-performance applications and performance debugging/optimization for CPUs/GPUs.
  • Experience with DNN/LLM inference and familiarity with DL frameworks like PyTorch, TensorFlow, ONNX Runtime, CUDA, ROCm, Triton.
  • Solid foundation in software engineering principles, computer architecture, GPU architecture, and hardware neural net acceleration.
  • Proficiency in end-to-end performance analysis and optimization of state-of-the-art LLMs and HPC applications using GPU profiling tools.

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