The Sr. AI Accelerator Tools Development Engineer will lead the development of stress, validation, and performance tooling for MAIA AI accelerator platforms within the Platform Systems Engineering team. This role involves building software frameworks and tools that exercise various layers of the AI stack, contributing to platform bring-up, qualification, and performance characterization. The engineer will collaborate closely with silicon architects, compiler teams, and AI framework developers to translate platform requirements into effective tooling solutions. The focus is on optimizing AI workloads and ensuring the reliability and performance of next-generation AI systems.

• Doctorate in Electrical Engineering, Computer Engineering, Computer Science, or related field AND 1+ year(s) technical engineering experience OR Master's Degree in the same fields AND 4+ years technical engineering experience OR Bachelor's Degree in the same fields AND 5+ years technical engineering experience OR equivalent experience.
• 4+ years of experience with programming skills in C/C++ and Python, with experience designing and developing production-quality software systems.
• 4+ years of experience developing, debugging, or optimizing AI workloads for GPUs, AI accelerators, or HPC systems.
• 4+ years of experience with accelerator architecture and performance optimization.

• Design and develop scalable stress, performance, and validation frameworks for MAIA AI accelerator platforms.
• Build workload generation infrastructure capable of exercising compute, memory, interconnect, networking, storage, and system-level resources.
• Develop reusable stress tools using PyTorch, Triton, Python, C++, and custom MAIA SDKs.
• Create synthetic and production-inspired workloads that model training and inference behaviors.
• Build automated infrastructure for workload deployment, orchestration, telemetry collection, and result analysis.
• Develop and optimize kernels targeting custom AI accelerators.
• Analyze execution behavior across the hardware-software stack and identify bottlenecks impacting utilization and performance.
• Develop tooling that integrates with MAIA compiler pipelines, SDKs, runtime environments, and performance analysis tools.
• Design workload suites for platform bring-up, qualification, and reliability testing.
• Characterize system performance across compute, networking, memory, and storage subsystems.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.