Microsoft AI is looking for a Member of Technical Staff, Compute Orchestration & Scheduling, to help build the next generation of AI infrastructure powering frontier model development. The Compute Orchestration & Scheduling team own cluster orchestration, workload scheduling, resource allocation, quota management, and the systems that enable fast initialization and reliable fault recovery for Ray and Kubernetes workloads running on next-generation GPU supercomputers.
Our team develops the systems required to make AI infrastructure ready for the next generation of distributed training and inference workloads, spanning multiple locations with a massive and rapidly growing fleet of advanced accelerators across multiple hardware generations, including NVIDIA Grace Blackwell, Vera Rubin, and/or AMD GPU platforms, as well as accompanying CPU, Network and Storage infrastructure.
Key challenges include topology-aware placement, large-scale distributed training, fast and reliable initialization of Ray and Kubernetes environments, rapid fault recovery for long-running AI jobs, deep observability into cluster behavior, and continuously improving utilization across increasingly large accelerator fleets. Every improvement in scheduling efficiency, platform reliability, and cluster utilization directly increases the effective compute available for frontier AI research and product development.
You'll wear multiple hats and partner closely with researchers, model engineers, hardware architects, and infrastructure teams to translate the needs of frontier model development into scalable platform capabilities. You'll be expected to find paths around roadblocks, get solutions into users' hands quickly and iteratively, and thrive in a fast-paced, design-driven product development environment. We are looking for engineers who are excited by challenging systems problems, comfortable operating in ambiguous environments, and motivated by building infrastructure that directly accelerates frontier AI model development.
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
- Develop and tune the pretraining scalable software for Nvidia Grace-Blackwell (GB), Vera-Rubin (VR) and AMD MIxxx architectures
- Scale GB, VR and AMD MIxxx GPU clusters beyond thousands of GPUs
- Gather data and insights to develop the GPU & CPU compute roadmap suitable for large-scale AI labs
- Actively contribute to the development of AI models that are powering our innovative products
- Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively
- Enjoy working in a fast-paced, design-driven, product development cycle
- Embody our Culture and Values
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, C++, Python, Go or JavaScript
- OR equivalent experience.
- 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++, Python, Go or JavaScript
- OR equivalent experience.
- Expertise in one of Ray, Kubernetes, Kueue, Volcano, or any other AI-focused systems for scheduling / scaling / fault-tolerance.
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 IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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.
Similar Jobs
What you need to know about the Colorado Tech Scene
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
