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Software Co-Design AI HPC Systems

Job in Redmond, King County, Washington, 98073, USA
Listing for: Microsoft Corporation
Full Time position
Listed on 2026-06-06
Job specializations:
  • IT/Tech
    Systems Engineer, AI Engineer
Job Description & How to Apply Below
** Overview*
* Our team's mission is to architect, co-design, and product ionize next-generation AI systems at datacenter scale. We operate at the intersection of models, systems software, networking, storage, and AI hardware, optimizing end-to-end performance, efficiency, reliability, and cost. Our work spans today's frontier AI workloads and directly shapes the next generation of accelerators, system architectures, and large-scale AI platforms. We pursue this mission through deep hardware-software co-design, combining rigorous systems thinking with hands-on engineering.

The team invests heavily in understanding real production workloads large-scale training, inference, and emerging multimodal models and translating those insights into concrete improvements across the stack: from kernels, runtimes, and distributed systems, all the way down to silicon-level trade-offs and datacenter-scale architectures.

This role sits at the boundary between exploration and production. You will work closely with internal infrastructure, hardware, compiler, and product teams, as well as external partners across the hardware and systems ecosystem. Our operating model emphasizes rapid ideation and prototyping, followed by disciplined execution to drive high-leverage ideas into production systems that operate at massive scale.

In addition to delivering real-world impact on large-scale AI platforms, the team actively contributes to the broader research and engineering community. Our work aligns closely with leading communities in ML systems, distributed systems, computer architecture, and high-performance computing, and we regularly publish, prototype, and open-source impactful technologies where appropriate.

** Microsoft Superintelligence Team*
* Microsoft Superintelligence team'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.

This role is part of Microsoft AI's Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence-ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society-advancing science, education, 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*
* + Lead the co-design of AI systems across hardware and software boundaries, spanning accelerators, interconnects, memory systems, storage, runtimes, and distributed training/inference frameworks.

+ Drive architectural decisions by analyzing real workloads, identifying bottlenecks across compute, communication, and data movement, and translating findings into actionable system and hardware requirements.

+ Co-design and optimize parallelism strategies, execution models, and distributed algorithms to improve scalability, utilization, reliability, and cost efficiency of large-scale AI systems.

+ Develop and evaluate what-if performance models to project system behavior under future workloads, model architectures, and hardware generations, providing early guidance to hardware and platform roadmaps.

+ Partner with compiler, kernel, and runtime teams to unlock the full performance of current and…
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