Principal Silicon Performance Architect

Job Title

Principal Silicon Performance Architect

Role Summary

Join a small engineering team focused on AI performance across silicon, systems, and software. The role owns performance modeling and analysis for AI inference workloads, translating architectural ideas into simulator implementations, running experiments across design variants, and delivering data-driven guidance for architecture and product decisions.

Experience Level

Senior individual contributor. The posting requests 8+ years of technical engineering experience or equivalent practical experience.

Responsibilities

Primary responsibilities include developing simulators, running experiments, and communicating results to influence architecture decisions.

• Extend and adapt simulation infrastructure to model micro-architecture innovations for AI inference.
• Analyze performance across latency, throughput, and efficiency for current and future AI inference workloads.
• Drive design-space exploration using automation, AI-assisted workflows, and large-scale experiment generation.
• Communicate performance insights clearly and provide data-driven recommendations to influence architecture decisions.
• Collaborate with chip, system, and software architects to propose, evaluate, and iterate on architectural variations.

Requirements

Must-have technical skills and conditions are listed first; preferred skills follow.

• Proven software development experience in system-level languages such as C, C++, and Python.
• Experience in performance engineering: profiling, bottleneck analysis, experimental design, and micro-architecture trade-off analysis.
• Experience using or modifying performance modeling or simulation frameworks to evaluate hardware/software trade-offs.
• Experience with AI inference acceleration features and accelerator/GPU performance analysis and with the AI inference software stack (compilers, runtimes, model serving).
• Ability to collaborate cross-functionally with chip, system, and software teams and to turn experimental results into actionable guidance.
• Ability to meet Microsoft Cloud Background Check and other required security screening.
• Nice-to-have: experience in chip/micro-architecture analysis at the logical level (memory, functional units, memory controllers, I/O); experience modifying architectural simulators; experience with AI-assisted workflows and large-scale experiment automation.

Education Requirements

Minimum: Bachelor's degree in Computer Science or a related technical field AND 8+ years of technical engineering experience, or equivalent practical experience. Preferred: Advanced degree (Master's or Ph.D.) in Electrical Engineering, Computer Engineering, or a related field.

About the Company

Company: Microsoft

Headquarters: Redmond, Washington, United States

Microsoft is a global technology company that develops and sells software, services, devices, and solutions. Known for its Windows operating system, Office suite, and Azure cloud platform, Microsoft aims to empower individuals and organizations around the world to achieve more. The company fosters a culture of innovation and inclusion, focusing on delivering trusted experiences to customers and partners globally.