Senior and/or Principal Software Engineer - AI Frameworks
Microsoft (Eightfold Apply)
- Location
- United States, Multiple Locations, Multiple Locations
- Work model
- On-Site
- Level
- Principal
- Posted
- 2h ago
Skills
About this role
Overview
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 E ngineers - 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.
Responsibilities
As a Senior Software Enginer: 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. As a Principal Software Engineer: 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;