Principal Software Engineer, Performance Tooling

Microsoft

Quick summary

Work type
On-site
Location
Redmond, WAMountain View, CA
Salary
$165,600–$296,400 / yr
Posted
8 days ago
Closes
Dec 16, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $201k
This role $231k
$130k most similar roles pay here $314k

This role pays more than 79% of similar roles. Most pay $179,075–$223,700 — the shaded band above. At the midpoint, this role pays about $231k versus about $201k 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 an AI Infrastructure Software Engineering IC5, you will lead the technical strategy for AI performance tooling and validation across various layers of the software stack, including models, compilers, runtimes, libraries, and APIs. Your day-to-day responsibilities include conducting deep performance investigations to optimize production-scale training and inference, establishing quality standards, and mentoring engineers to raise the technical bar. You will work with C++, Python, PyTorch, TensorFlow, CUDA, ROCm, and Triton, among other technologies, to build high-performance distributed systems for AI workloads. This role requires a deep understanding of DNN/LLM inference or training performance, software engineering, distributed systems, GPU architecture, and hardware/software co-design. You will influence technical strategy across organizations, lead multi-team initiatives, and drive alignment with senior stakeholders to ensure measurable impact on performance, reliability, cost efficiency, and developer productivity in the AI domain.

What you'll do

  • Define and drive technical strategy for AI performance tooling and validation.
  • Lead deep performance investigations to guide teams toward durable optimizations.
  • Establish quality bars and readiness signals for faster model bring-up.
  • Mentor engineers by modeling excellence, improving design quality, and creating reusable systems.
  • Independently lead multi-team initiatives with measurable impact on cost efficiency and productivity.

What we're looking for

  • 8+ years experience in building and optimizing high-performance distributed systems.
  • Deep expertise in DNN/LLM inference/training performance with major deep learning frameworks.
  • Strong background in software engineering, distributed systems, and hardware/software co-design.
  • Proven ability to lead end-to-end performance analysis for state-of-the-art AI services.
  • Recognized technical depth in GPU/accelerator architecture and programming environments.
  • Demonstrated leadership in driving technical strategy and alignment across organizations.
  • Track record of independently leading initiatives with measurable impact on performance.

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