Full Stack ML Efficiency & Observability
Microsoft · United States, Multiple Locations, Multiple Locations ·
- Work mode
- Onsite
- Category
- Fullstack
- Experience
- 4+ years
Microsoft · United States, Multiple Locations, Multiple Locations ·
Microsoft AI is looking for a Member of Technical Staff - Full Stack Engineer, ML Efficiency & Observability to help us efficiently manage our compute capacity. We’re looking for someone who will bring an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective. The right candidate enjoys building world-class consumer experiences and products in a fast-paced environment. You will wear multiple hats and work on engineering, research, and everything in between. Your contributions will span capacity, efficiency, data architecture, training and inference infrastructures, and many other exciting topics at the cutting edge of AI.
Microsoft AI is building foundational models to develop novel responsible and efficient artificial general intelligence. The foundational models require large compute-capacity, and as a Senior Engineer – Full Stack, ML Efficiency & Observability you will be responsible for building world-class user experience for our executives as well as out ML researcher. You’ll work closely with research and framework teams to turn their requirements into intuitive experiences that lead to efficiency improvements. As a contributing member of the core group of engineers, you would also bring to the table best practices driving architectural changes and influence roadmap of relevant software components.
Microsoft AI
This role is part of Microsoft AI. Our Superintelligence team is a startup-like organization within Microsoft, dedicated to pushing the boundaries of artificial intelligence while maintaining a strong commitment to safety, responsibility, and human values.
Our mission is to build AI that amplifies human potential and empowers people around the world. We strive to deliver breakthroughs that advance science, education, productivity, and global well-being.
We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!
MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.
Design and develop features for our capacity management portal
Design and develop features to provide visibility into model performance and quality across our fleet
Partner with ML researchers and PMs to translate functional requirements into highly functional, intuitive and appealing interfaces
Integrate with backend APIs from schedulers to training frameworks to build visibility across the training life cycle
Explore, develop, and adapt new innovations to the software development process
Contribute to the development of internal tooling and infrastructure
Implement best software development practices to ensure code quality. Hold a high quality bar.
Embody our culture and values.
Required Qualifications:
Preferred Qualifications:
Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling or data engineering work
OR Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years of business analytics, data science, software development, data modeling or data engineering work experience
OR equivalent experience.
Experience with Capacity Management, Efficiency Management, ML Training and/or Inference
Solid expertise in JavaScript / TypeScript, React, HTML, CSS and browser internals
Solid understanding of web performance, accessibility, and cross‑browser compatibility
Experience with Development & Debugging with dev environments like Visual Studio or Visual Studio Code
Software development experience with Generative AI tools
Experience in leading technical projects and supporting architectural decisions with data.
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:
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 per year.
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.
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.