Senior AI Hardware Architect | Microsoft Careers

Microsoft

Quick summary

Work type: On-site
Location: Redmond, WA
Salary: $119,800–$234,700 / yr
Posted: 3 days ago
Closes: Dec 9, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $211k

This role $177k

$103k most similar roles pay here $280k

This role pays less than 70% of similar roles. Most pay $177,250–$245,287 — the shaded band above. At the midpoint, this role pays about $177k versus about $211k for comparable roles.

Based on 240 similar postings.

Employer

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 1580 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 1408 roles with salary data.

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At a glance

TL;DR · Senior AI Hardware Architect | Microsoft Careers

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The Senior AI Hardware Architect position within the AI Systems Architecture (ASA) group involves driving analytical performance modeling and workload characterization across GPU and accelerator architectures. This role requires identifying performance bottlenecks, evaluating new architectural features, and optimizing memory and communication subsystems to enhance efficiency and scalability in large-scale AI systems. The ideal candidate will have expertise in GPU and AI accelerator architectures, proficiency in Python and C/C++, and experience with modern AI frameworks like PyTorch and vLLM. They will collaborate closely with various engineering teams to develop performance modeling tools and present findings to senior leadership, contributing to the design of future AI accelerator platforms that address complex business challenges in high-performance computing environments.

Skills

Python C/C++ GPU AI_accelerators Performance_modeling Architectural_simulation Workload_characterization Silicon_correlation Performance_profiling Benchmarking Hardware_counters Software_traces AI_kernels Performance_analysis_tools PyTorch vLLM SGLang Quantization Sparsity Sharding_strategies KV-cache_management Flash_Attention Communication_computation_overlap

What you'll do

Lead performance analysis and modeling of GPU and AI accelerator architectures, identifying bottlenecks.
Analyze end-to-end AI workloads to understand performance drivers and optimization opportunities.
Develop models to evaluate new architectural features and innovations in memory and interconnects.
Correlate silicon measurements with software traces to improve model fidelity for future architecture decisions.
Drive kernel-level optimizations across AI training and inference workloads, translating insights into improvements.
Design data analysis tools that enhance debugging efficiency and architectural insight for performance modeling.

What we're looking for

Master's Degree in Electrical/Computer/Mechanical Engineering or equivalent experience.
3+ years of technical engineering experience with a focus on AI systems and computer architecture.
Strong understanding of GPU and AI accelerator architectures, including memory hierarchies and interconnects.
Experience with analytical performance modeling, workload characterization, and silicon correlation for system design.
Expertise in performance profiling, benchmarking, and root-cause analysis using hardware counters and software traces.
Hands-on experience analyzing and optimizing AI kernels across various execution models.
Strong programming skills in Python and C/C++ for developing performance analysis tools and automation scripts.

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