Principal Software Engineer - Performance Tooling

Reposted 2 Days Ago
Be an Early Applicant
2 Locations
In-Office
143K-331K Annually
Expert/Leader
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Develop performance tooling for large-scale AI model training and inference. Benchmark, profile, debug, and optimize OpenAI and other LLM workloads across CPUs, GPUs, and Microsoft hardware. Work across compilers, runtimes, libraries, APIs, and other AI software layers to identify regressions, reduce deployment time and hardware requirements, and deliver scalable production improvements. Lead projects and collaborate with researchers, engineers, hardware teams, and external partners.
Summary Generated by Built In
Overview

The Artificial Intelligence (AI) Frameworks team at Microsoft develops AI software that enables running AI models everywhere, from world’s fastest AI supercomputers, to servers, desktops, mobile phones, internet of things (IoT) devices and internet browsers. We collaborate with our hardware teams and partners, both internal and external, and operate at the intersection of AI algorithmic innovation, purpose-built AI hardware, systems, and software. We are a team of highly capable and motivated people that pride themselves on a collaborative and inclusive culture.  We own inference performance of OpenAI and other state of the art large language model (LLM) models and work directly with OpenAI on the models hosted on the Azure OpenAI service serving some of the largest workloads on the planet with trillions of inferences per day in major Microsoft products, including Office, Windows, Bing, SQL Server, and Dynamics. 


As a Principal Software Engineer - Performance Tooling on the team, you will have the opportunity to work on multiple levels of the AI software stack, including the fundamental abstractions, programming models, compilers, runtimes, libraries and application programming interfaces (APIs) to enable large scale training and inferencing of models. You will benchmark OpenAI and other LLM models for performance on graphics processing units (GPUs) and Microsoft hardware, debug and optimize performance, monitor performance and enable these models to be deployed in the shortest amount of time and the least amount of hardware possible helping achieve Microsoft Azure's capex goals.


Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. 


Responsibilities
  • Work across multiple layers of the AI software stack (abstractions, programming models, compilers, runtimes, libraries, and APIs) to enable large-scale model training and inference.
  • Benchmark OpenAI and other LLMs for performance on Graphic Processing Units (GPUs) and Microsoft hardware.
  • Debug, profile, and optimize performance for training/inference workloads on CPUs (Central Processing Units)/GPUs.
  • Monitor performance regressions and drive continuous improvements to reduce time-to-deploy and hardware footprint.
  • Collaborate across teams of researchers and engineers to deliver scalable, production-ready AI performance improvements.

Qualifications

Required/Minimum Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, or Python OR equivalent experience.


Other Requirements:

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. This includes passing the Microsoft Cloud background check upon hire/transfer and every two years thereafter.


Preferred/Additional Qualifications:

  • Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C++, or Python
    • OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C++, or Python
    • OR equivalent experience.
  • 4+ years’ practical experience working on high performance applications and performance debugging and optimization on CPUs/GPUs.
  • Experience in DNN/LLM inference and experience in one or more DL frameworks such as PyTorch, Tensorflow, or ONNX Runtime and familiarity with CUDA, ROCm, Triton.
  • Technical background and solid foundation in software engineering principles, computer architecture, GPU architecture, hardware neural net acceleration.
  • Experience in end-to-end performance analysis and optimization of state of the art LLMs and HPC applications, including proficiency using GPU profiling tools.
  • Cross-team collaboration skills and the desire to collaborate in a team of researchers and developers.
  • Ability to independently lead projects.

#AIInfra



Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Skills Required

  • Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience with coding in C++, Python, or similar languages, or equivalent experience
  • Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud background check
  • Master's degree in Computer Science or a related technical field and 12+ years of technical engineering experience, or bachelor's degree and 15+ years of experience, or equivalent experience
  • 4+ years of practical experience with high-performance applications, performance debugging, and CPU/GPU optimization
  • Experience with DNN/LLM inference and one or more deep learning frameworks such as PyTorch, TensorFlow, or ONNX Runtime
  • Familiarity with CUDA, ROCm, and Triton
  • Strong foundation in software engineering, computer architecture, GPU architecture, and hardware neural network acceleration
  • Experience analyzing and optimizing end-to-end performance of state-of-the-art LLMs and HPC applications, including GPU profiling tools
  • Cross-team collaboration skills and willingness to collaborate with researchers and developers
  • Ability to independently lead projects

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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