Senior and/or Principal Software Engineer - AI Frameworks
About The Position
The Microsoft AI Frameworks team develops software, performance systems, and engineering tools that enable state-of-the-art AI models to run reliably and efficiently at cloud scale. The team works across model architectures, frameworks, compilers, runtimes, libraries, observability, benchmarking, and hardware platforms, including NVIDIA and AMD GPUs and Microsoft silicon. Engineers partner with model developers, researchers, hardware teams, and production services to accelerate model onboarding, improve performance and reliability, reduce deployment time and hardware footprint, and turn performance insights into durable platform capabilities. This is a hands-on individual-contributor role for engineers who enjoy solving ambiguous, end-to-end systems problems. The Senior Software Engineer owns significant components and projects across AI performance, benchmarking, automation, and developer tooling, translating model and platform needs into robust software and investigating complex performance and reliability issues. The Principal Software Engineer sets technical direction and leads high-impact initiatives across AI frameworks, performance engineering, benchmarking, and tooling, while remaining hands-on in the design and delivery of solutions that improve model velocity, platform efficiency, and production reliability. The role requires collaboration across organizational boundaries to deliver production impact and support Microsoft's mission and culture. Applicants must meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Requirements
- Bachelor's degree in Computer Science or a related technical field and 4+ years of technical engineering experience coding in languages such as C++ or Python, or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Nice To Haves
- Experience building and operating complex software systems.
- Practical knowledge of performance analysis, benchmarking, automation, or developer tooling.
- Familiarity with AI/ML frameworks such as PyTorch, TensorFlow, or ONNX Runtime.
- Familiarity with GPU software and profiling technologies such as CUDA, ROCm, Triton, or equivalent.
- Demonstrated cross-team collaboration and technical ownership.
- For Principal-level work: extensive experience designing and shipping complex, high-performance or distributed software systems.
- For Principal-level work: experience in software architecture, computer architecture, and accelerator-aware optimization.
- For Principal-level work: experience with AI/ML workloads and frameworks.
- For Principal-level work: demonstrated leadership of cross-team technical initiatives from strategy through production.
- For Principal-level work: track record of creating reusable platforms, influencing senior stakeholders, and mentoring technical leaders.
Responsibilities
- Design, implement, test, and operate production-quality components across AI frameworks, runtimes, benchmarking systems, performance tooling, and service integrations.
- Benchmark, profile, debug, and optimize large language model training and inference workloads across GPUs and Microsoft hardware.
- Build automation and observability to detect regressions, improve reproducibility, surface actionable insights, and accelerate model and hardware onboarding.
- Drive scoped projects from problem definition through deployment, balancing delivery speed, maintainability, reliability, and measurable customer or capacity impact.
- Partner with researchers, model teams, infrastructure owners, and hardware vendors to diagnose cross-stack issues and deliver production-ready solutions.
- Contribute to technical design reviews, engineering standards, operational health, and mentoring of other engineers.
- For Principal-level work, define technical vision, architecture, and multi-release strategy for critical AI framework, performance, benchmarking, or developer-productivity capabilities.
- Lead ambiguous, cross-stack investigations and investments spanning models, frameworks, compilers, runtimes, systems, services, and silicon.
- Establish common measurement, automation, observability, and engineering mechanisms that turn one-off analyses into scalable platform capabilities.
- Drive measurable improvements in model onboarding velocity, runtime performance, reliability, hardware utilization, and Azure capacity efficiency.
- Influence architecture and priorities across teams; align researchers, product groups, infrastructure owners, and hardware partners around clear decisions and execution plans.
- Provide hands-on technical leadership through prototypes, critical-path implementation, design and code reviews, complex debugging, and operational readiness.
- Mentor senior engineers, develop technical leaders, and advance standards for quality, maintainability, and inclusive collaboration.
- Embody Microsoft's culture and values.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
