The Member of Technical Staff, Pre-Training Infrastructure at Microsoft AI will contribute to the development of capabilities for the personalized AI assistant, Copilot. This role focuses on building and optimizing software for large-scale GPU clusters and high-throughput storage systems. The ideal candidate will work closely with model scientists to enhance distributed training and ensure the performance of thousands of GPUs. This position is part of a team dedicated to advancing consumer AI products and research.

• Bachelor's Degree in Computer Science or related technical field AND 6+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python.
• Master's Degree in Computer Science or related technical field AND 8+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python.
• 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.

• Design, implement, test, and optimize distributed training infrastructure in Python and C++ for large-scale GPU clusters.
• Profile, benchmark, and debug performance bottlenecks across compute, memory, networking, and storage subsystems.
• Optimize collective communication libraries for emerging NVLink and InfiniBand topologies.
• Collaborate with hardware teams to optimize for next-generation accelerators.
• Gather data and insights to develop the pretraining compute roadmap.
• Actively contribute to the development of AI models powering innovative products.
• Find solutions to overcome roadblocks and deliver work quickly and iteratively.
• Embody the culture and values of Microsoft.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.