Principal Software Engineer, Performance Tooling

Microsoft

Quick summary

Work type
On-site
Location
US
Salary
$142,800–$274,800 / yr
Posted
5 days ago
Closes
Dec 19, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $203k
This role $209k
$127k most similar roles pay here $291k

This role pays more than 59% of similar roles. Most pay $180,862–$226,050 — the shaded band above. At the midpoint, this role pays about $209k versus about $203k for comparable roles.

Based on 239 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 622 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 571 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer, Performance Tooling

As a Principal Software Engineer 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 training and inference of AI models. Your daily tasks will involve benchmarking OpenAI and other LLMs for performance on GPUs and Microsoft hardware, debugging and optimizing their performance, and monitoring regressions to ensure continuous improvements in deployment speed and efficiency. You will collaborate closely with researchers and engineers to deliver scalable, production-ready solutions that support major Microsoft products like Office, Windows, Bing, SQL Server, and Dynamics. The role requires expertise in C++ or Python, experience with high-performance applications on CPUs/GPUs, familiarity with DL frameworks such as PyTorch, TensorFlow, or ONNX Runtime, and proficiency using GPU profiling tools for end-to-end performance analysis and optimization of state-of-the-art LLMs and HPC applications.

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 to reduce time-to-deploy.
  • Develop scalable, production-ready AI performance enhancements across the software stack.
  • Collaborate with researchers and engineers to deliver high-performance AI solutions.

What we're looking for

  • Master's Degree in Computer Science or related field with 12+ years experience, or Bachelor's with 15+ years experience in technical engineering.
  • Extensive coding experience in C++, Python, and other relevant languages.
  • At least 4 years of practical experience in high-performance application development and performance debugging on CPUs/GPUs.
  • Proficiency in DNN/LLM inference and familiarity with DL frameworks like PyTorch, TensorFlow, ONNX Runtime, CUDA, ROCm, Triton.
  • Strong foundation in software engineering principles, computer architecture, GPU architecture, and hardware neural net acceleration.
  • Experience 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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