Member of Technical Staff, LLM Inference - MAI Superintelligence Team at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Mar, 26

Salary

274800.0

Posted On

18 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Open-Source Inference Frameworks, Python, GPU Kernel Programming, Distributed Computing, Performance Optimization, Debugging, Model Inference, FastAPI, Profiling, JAX, C, C++, C#, Java, JavaScript

Industry

Software Development

Description

Overview Our Inference team is responsible for building and maintaining the tools and systems that enable Microsoft AI researchers to run models easily and efficiently. Our work empowers researchers to run models in RL, synthetic data generation, evals, and more. We are joint stewards of one of the largest compute fleets in the world. The team is responsible for optimizing compute efficiency on our heterogeneous data centers as well as enabling cutting-edge research and production deployment. We are an applied research team that is embedded directly in Microsoft AI’s research org to work as closely as possible with researchers. We are vertically integrated, owning everything from kernels to architecture co-design to distributed systems to profiling and testing tools. This role could be a great match for you if you: Understand modern generative AI architectures and how to optimize them for inference. Are familiar with the internals of open-source inference frameworks like vLLM and SGLang. Value clear communication, improving team processes, and being a supportive team player. Are results-oriented, have a bias toward action, and enjoy owning problems end-to-end. Have or can quickly gain familiarity with modern Python and its tooling, PyTorch, Nvidia GPU kernel programming and optimization, Infiniband, and NVLink. Our newly formed parent organization, Microsoft AI (MAI), is dedicated to advancing Copilot and other consumer AI products and research. The team is responsible for Copilot, Bing, Edge, and AI research. Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction. Responsibilities Work alongside researchers and engineers to implement frontier AI research ideas. Introduce new systems, tools, and techniques to improve model inference performance. Build tools to help debug performance bottlenecks, numeric instabilities, and distributed systems issues. Build tools and establish processes to enhance the team’s collective productivity. Find ways to overcome roadblocks and deliver your work to users quickly and iteratively. Enjoy working in a fast-paced, design-driven product development cycle. Embody our Culture and Values. Qualifications Required 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, C++, C#, Java, JavaScript, or Python OR equivalent experience. Preferred qualifications Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor'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, C++, C#, Java, JavaScript, or Python OR equivalent experience. Experience with generative AI. Experience with distributed computing. Python and Python ecosystem (eg. uv, pybind/nanobind, FastAPI) expertise. Experience with large scale production inference. Experience with GPU kernel programming. Experience benchmarking, profiling, and optimizing PyTorch generative AI models. Experience with open source inference frameworks like vLLM and SGLang. Working experience and conversant with the material in the JAX scaling book. Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $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 $163,000 - $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.

Responsibilities

Work alongside researchers and engineers to implement frontier AI research ideas and introduce new systems, tools, and techniques to improve model inference performance. Build tools to help debug performance bottlenecks and enhance the team’s collective productivity.