Job description

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 Software 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. 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. 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 • 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.  Qualifications Required/Minimum Qualifications: • 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. Other Requirements: • 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. Additional or Preferred qualifications: • Expertise in GPU or equivalent accelerator programming and kernel optimization using CUDA, Triton, or comparable technologies. • Experience using profiling and benchmarking to deliver measurable performance improvements, with an understanding of memory hierarchy, parallel execution, synchronization, and hardware utilization. • Familiarity with vLLM, SGLang, or equivalent inference frameworks, including their model execution, scheduling, batching, and KV-cache mechanisms. • Demonstrated technical ownership and cross-team collaboration, including independently delivering complex engineering changes into production. • Ability to use AI-assisted development tools effectively while maintaining sound engineering judgment and accountability for correctness, performance, and maintainability #AIInfra Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: careers.microsoft.com This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Requirements

Must-haves

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.
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.
Expertise in GPU or equivalent accelerator programming and kernel optimization using CUDA, Triton, or comparable technologies.
Experience using profiling and benchmarking to deliver measurable performance improvements, with an understanding of memory hierarchy, parallel execution, synchronization, and hardware utilization.
Familiarity with vLLM, SGLang, or equivalent inference frameworks, including their model execution, scheduling, batching, and KV-cache mechanisms.
Demonstrated technical ownership and cross-team collaboration, including independently delivering complex engineering changes into production.
Ability to use AI-assisted development tools effectively while maintaining sound engineering judgment and accountability for correctness, performance, and maintainability
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipython

Platform: eightfold
Effort: medium