Microsoft AI is looking for a Member of Technical Staff, Pre-Training Infrastructure, to help build the next wave of capabilities for our personalized AI assistant, Copilot. We’re seeking someone who brings an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective. The ideal candidate enjoys building world-class consumer experiences and products in a fast-paced environment. You will actively contribute to the development of AI models powering our innovative products. Expect to wear multiple hats and work across engineering, research, and everything in between. Your contributions will span model architecture, data curation, training and inference infrastructure, evaluation protocols, alignment and reinforcement learning from human feedback (RLHF), and many other exciting topics at the cutting edge of AI.

Microsoft AI is building the training infrastructure that powers frontier-scale models and advances research toward humanist superintelligence. As a Member of Technical Staff, Pre-Training Infrastructure, you will contribute to a fast-moving codebase that enables training at unprecedented scale. This role focuses on building and optimizing the software stack for massive GPU clusters, high-throughput storage systems, and cutting-edge AI research. You will work closely with model scientists to scale up the latest research recipes, implement new forms of distributed training parallelism, and ensure the reliability and performance of thousands of GPUs across our supercomputing fleet. Profiling, benchmarking, debugging, and fine-grained optimization are core to this role, demanding both engineering rigor and creativity.

As a contributing member of the core engineering group, you will also bring best practices, drive architectural changes, and influence the roadmap for relevant software and hardware components. Your work will directly impact business goals for a wide range of users and facilitate the next wave of growth and innovation in AI.

Our newly formed organization, Microsoft AI, is dedicated to advancing Copilot and other consumer AI products and research. The team is responsible for Copilot, Bing, Edge, and generative AI research. Come be part of the team shaping the future of personal computing.

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.

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.

• 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 in distributed computing and large-scale systems.
• Experience with GPU programming (CUDA, NCCL) and frameworks such as PyTorch.
• Proven ability to profile, benchmark, and optimize performance-critical systems.
• Experience in leading technical projects and supporting architectural decisions with data.  
• Experience building infrastructure for large-scale machine learning or generative AI workloads.
• Experience in networking (InfiniBand, NVLink), storage systems, or distributed training parallelisms.
• Track record of contributing to high-performance computing or large-scale AI infrastructure projects.