Pre-Training Infrastructure
Microsoft· startup· Software· Nov 25, 2025 · 11mo agoPosted 336 days ago
United States, Multiple Locations, Multiple Locations
In office
Full-time
Senior
$165K–$215K est.
6+ years exp
Before you apply
Ghost Signal:
Open since November 25, 2025 — 336 days, and still accepting applications.
Job description
Overview
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.
Microsoft AI
This role is part of Microsoft AI. Our team is a startup-like organization within Microsoft, dedicated to pushing the boundaries of artificial intelligence while maintaining a strong commitment to safety, responsibility, and human values.
Our mission is to build AI that amplifies human potential and empowers people around the world. We strive to deliver breakthroughs that advance science, education, productivity, and global well-being.
We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!
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
• 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 (e.g., NCCL) for emerging NVLink and InfiniBand topologies.
• Collaborate with hardware teams to optimize for next-generation accelerators (NVIDIA, AMD, and beyond).
• Gather data and insights to develop the pretraining compute roadmap.
• Care deeply about conversational AI and its deployment.
• Actively contribute to the development of AI models powering our innovative products.
• Find solutions 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/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++, 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.
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:
careers.microsoft.com
Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $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:
careers.microsoft.com
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.
Application prep
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Keywords to mirror
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