Partner across model, runtime, infrastructure, and hardware teams to remove obstacles and deliver production impact.
How We Work
We work across the entire software stack, from model architectures and serving systems to infrastructure and hardware interactions.
The problems we solve evolve throughout the lifecycle of both models and hardware platforms. Engineers on the team regularly become effective in new domains and develop deep expertise when needed.
We rely heavily on measurement, experimentation, automation, and AI-assisted engineering workflows to move quickly and scale our impact.
We partner closely with model, software, and hardware teams to deliver production-ready solutions.
Success Looks Like
A new model architecture can run correctly on Maia.
Production models achieve performance, scalability, and reliability targets.
Bottlenecks are identified and resolved regardless of where they exist in the stack.
New hardware generations become usable by model teams.
Model onboarding becomes faster, more repeatable, and less operationally intensive.
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
Understanding of modern AI model architectures, inference systems, and performance characteristics.
Experience working with AI/ML frameworks, runtimes, or serving stacks such as PyTorch, ONNX Runtime, vLLM, TensorRT-LLM, or similar technologies.
Experience diagnosing and resolving complex issues across software, systems, and hardware layers.
Familiarity with performance analysis, distributed systems, accelerator architectures, or large-scale production services.
Experience enabling software on new hardware platforms, accelerators, or large-scale systems through activities such as bring-up, performance characterization, hardware-software debugging, or platform enablement.
Experience using AI-assisted engineering tools, agents, skills, and workflow automation to accelerate software development, debugging, code maintenance, investigation, and engineering productivity.
Proficiency in software development with languages such as Python, C++, or equivalent technologies.
#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:
- https://careers.microsoft.com/us/en/us-corporate-pay
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.
