The AI Frameworks team at Microsoft is focused on optimizing large language model deployment on custom AI accelerators and GPUs. They are seeking a self-motivated Senior Software Engineer who is passionate about technical innovation and thrives in a fast-paced environment. This role involves shaping the software that powers Microsoft's advanced AI infrastructure. The team values collaboration and inclusion, aiming to empower every person and organization.

• Bachelor's Degree in Computer Science or related technical field and 4+ years of technical engineering experience with coding in languages including C, C++, or Python.
• Master's Degree in Computer Science or related technical field and 6+ years of technical engineering experience with coding in languages including C, C++, or Python, or equivalent experience.
• Experience with PyTorch internals, custom operators, hardware backend, or torch.compile/Dynamo-based optimization flows.
• Experience with AI inference stacks such as vLLM, SGLang, or similar large-scale model serving systems.
• Experience with NPU or GPU kernel development and optimization, including CUDA, Triton, or accelerator-specific toolchains.
• Familiarity with common LLM concepts such as attention mechanisms, KV caching, quantization, and distributed parallelism strategies.

• Architect and implement efficient tensor computation primitives and software abstractions for custom AI accelerators.
• Develop and extend PyTorch features for model onboarding, optimization, and execution on custom AI accelerators.
• Contribute to and improve AI inference stacks such as vLLM and SGLang, including scheduling, KV cache management, and serving pipelines.
• Design, develop, profile, and optimize high-performance kernels for NPUs and GPUs to accelerate LLM inference and training workloads.
• Collaborate across disciplines to define requirements and deliver practical solutions to new technical challenges.

• 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.