Software Co-Design AI HPC Systems | Microsoft Careers

Microsoft

Hybrid

Quick summary

Work type
Hybrid
Location
Salary
$142,800–$274,800 / yr
Posted
113 days ago
Closes
Aug 11, 2026

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Competitive pay

How this pay compares to similar roles

Similar $206k
This role $209k
$127k most similar roles pay here $291k

This role pays more than 51% of similar roles. Most pay $177,250–$235,750 — the shaded band above. At the midpoint, this role pays about $209k versus about $206k for comparable roles.

Based on 240 similar postings.

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About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 310 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 285 roles with salary data.

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TL;DR · Software Co-Design AI HPC Systems | Microsoft Careers

As a senior AI systems architect at our cutting-edge team, you will lead the co-design of next-generation AI systems across hardware and software boundaries, focusing on accelerators, interconnects, memory systems, storage, runtimes, and distributed training frameworks. Your daily tasks include analyzing real workloads to identify bottlenecks and translating insights into actionable system requirements, optimizing parallelism strategies for large-scale AI platforms, and developing performance models to guide future hardware roadmaps. You will collaborate closely with compiler, kernel, and runtime teams to unlock the full potential of current and next-generation accelerators, influence AI hardware design at both system and silicon levels, and mentor senior engineers while setting technical direction across the organization. Proficiency in C/C++, CUDA, Python, and experience with distributed systems, high-performance computing, and ML systems is essential, as well as a deep understanding of large-scale AI clusters and LLMs.

What you'll do

  • Lead the co-design of AI systems across hardware and software boundaries.
  • Analyze real workloads to identify bottlenecks and translate findings into system requirements.
  • Optimize parallelism strategies and distributed algorithms for large-scale AI systems.
  • Develop performance models to guide future hardware and platform roadmaps.
  • Partner with teams to unlock full performance of current and next-gen accelerators.
  • Influence AI hardware design at system and silicon levels, including microarchitecture.
  • Lead cross-functional efforts to prototype and productionize high-impact co-design ideas.

What we're looking for

  • Strong background in AI accelerator or GPU architectures, distributed systems, and large-scale AI training/inference.
  • Proficiency in systems-level programming (C/C++, CUDA, Python) and performance-critical software development.
  • Experience designing or operating large-scale AI clusters for training or inference.
  • Deep familiarity with LLMs, multimodal models, recommendation systems, and their system implications.
  • Expertise in accelerator interconnects, communication stacks, and hardware–software co-design for AI workloads.
  • Proven ability to influence technical decisions across multiple organizational boundaries.
  • Background in performance modeling, capacity planning, and leading hardware roadmaps.

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