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About the Role
Microsoft AI is seeking engineers to develop the compute infrastructure for frontier-model development. The Compute Orchestration & Scheduling team manages cluster orchestration, workload scheduling, resource allocation, and fault recovery on next-generation GPU supercomputers, supporting diverse hardware like NVIDIA Grace Blackwell and AMD GPUs.
Responsibilities
- Develop and tune the compute infrastructure stack for allocating NVIDIA Grace Blackwell (GB) and Vera Rubin (VR) resources to AI workloads.
- Scale GPU clusters across hardware generations to thousands of accelerators and beyond.
- Utilize operational data and workload insights to inform the compute (GPU and CPU) roadmap for large-scale AI research.
- Partner with model-development teams to enhance the infrastructure for training and serving AI models.
- Identify and overcome roadblocks, delivering rapid improvements through user iteration in a fast-paced environment.
- Embody Microsoft’s culture and values.
Requirements
- A bachelor’s degree in computer science or a related technical field.
- At least six years of engineering experience writing code in languages such as C, C++, Python, Go, or JavaScript; or equivalent practical experience.
- Significant additional engineering experience, with a master’s degree or equivalent practical experience, building production software and distributed systems.
- Experience with Ray, Kubernetes, Kueue, Volcano, or another AI-focused system for scheduling, scaling, or fault tolerance is especially relevant.
Skills
- C
- C++
- Python
- Go
- JavaScript
- Ray
- Kubernetes
- Kueue
- Volcano
Location
- United Kingdom
Work Type
- Full-time
Experience Level
- IC5
- 6+ years engineering experience
Education Level
- Bachelor's degree in Computer Science or related technical field
- Master's degree or equivalent practical experience (preferred)
Salary/Compensations
- £93,500.00 - £161,800.00 per year
Benefits
- Certain roles may be eligible for benefits and other compensation.
About the Company
- Microsoft AI is looking for engineers to build the compute infrastructure powering frontier-model development.
- Our team prepares infrastructure for the next generation of distributed training and inference across multiple locations and a rapidly growing fleet of accelerators, including NVIDIA Grace Blackwell, Vera Rubin, and AMD GPU platforms, alongside the CPU, network, and storage systems they depend on.
- Key challenges include topology-aware placement, large-scale distributed training, fast and reliable initialization of training runtimes, rapid recovery for long-running AI jobs, observability into cluster behavior, and improved utilization across increasingly large and diverse accelerator fleet.
- Better scheduling efficiency and platform reliability translate directly into more effective compute for AI research and products.
- You will work closely with researchers, model engineers, hardware architects, and infrastructure teams to turn frontier-model requirements into scalable platform capabilities.
- We value engineers who navigate ambiguity, remove roadblocks, and deliver improvements to users quickly and iteratively.
Equal Opportunity
- 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.