Senior and/or Principal Software Engineer - AI Frameworks

Microsoft•,

1d•$142,800 - $331,200

About The Position

The Microsoft AI Frameworks team develops the software, performance systems, and engineering tools that enable state-of-the-art AI models to run reliably and efficiently at cloud scale. We work across model architectures, frameworks, compilers, runtimes, libraries, observability, benchmarking, and hardware platforms—including NVIDIA and AMD GPUs and Microsoft silicon. Our Senior and/or Principal Software Engineers - AI Frameworks 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. Successful candidates combine strong software engineering fundamentals with curiosity about AI workloads, disciplined measurement, and a willingness to work across organizational boundaries to deliver production impact. As a Senior Software Engineer, you will own significant components and projects across AI performance, benchmarking, automation, and developer tooling. You will independently translate model and platform needs into robust software, investigate complex performance and reliability issues, and collaborate with partner teams to deliver measurable improvements into production. As a Principal Software Engineer, you will set technical direction and lead high-impact initiatives spanning AI frameworks, performance engineering, benchmarking, and tooling. You will identify systemic opportunities, align teams around durable architectures and success measures, and remain hands-on in the design and delivery of solutions that improve model velocity, platform efficiency, and production reliability. At Microsoft, our mission to empower every person and every organization on the planet to achieve more guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.

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 are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
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
Extensive experience designing and shipping complex, high-performance or distributed software systems
strong foundation in software architecture, computer architecture, and accelerator-aware optimization
experience with AI/ML workloads and frameworks
demonstrated leadership of cross-team technical initiatives from strategy through production
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 that 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.
Embody Microsoft’s culture and values.
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.
Raise the engineering bar by mentoring senior engineers, developing technical leaders, and advancing standards for quality, maintainability, and inclusive collaboration.