The Senior Machine Learning Engineer will design, build, deploy, and scale production machine learning systems. This is a deeply technical, hands-on role for an engineer with experience transforming machine learning models and research innovations into reliable product capabilities.
The ideal candidate has experience building systems across the machine learning lifecycle, including data processing, model training, evaluation, inference, and production operation. They will partner closely with applied scientists and software engineers to solve complex engineering problems spanning models, data, infrastructure, and services.
At the Senior level, this person will independently own major components and projects, make sound technical decisions, and drive complex work from design through production. They will contribute to the architecture of broader systems, coordinate work across components or partner teams, and develop reusable solutions that improve the team’s ability to build and operate machine learning capabilities.
This role is particularly suited to someone passionate about AI safety and Responsible AI and motivated to build systems that help advanced AI capabilities operate safely, reliably, and responsibly.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
- Design and build production systems for machine learning training, evaluation, inference, and operation.
- Transform machine learning models and research innovations into reliable, scalable product capabilities.
- Own complex engineering projects from technical design through implementation and production deployment.
- Develop infrastructure, services, and reusable components that support multiple models and workloads.
- Diagnose and resolve challenges involving system performance, scalability, reliability, and efficiency.
- Partner with applied scientists and software engineers to integrate modeling advances into production systems.
- Contribute to architectural decisions and coordinate technical work across components and partner teams.
- Incorporate security, privacy, safety, and Responsible AI considerations throughout system design and development.
- Mentor other engineers and contribute to strong engineering practices across the team.
Qualifications
- Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, 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
Preferred Qualifications:
- Master’s or Doctorate degree in Computer Science or a related technical field, with a focus on machine learning or related areas, AND 5+ years of technical engineering experience, or equivalent experience.
- Experience building machine learning infrastructure or platforms that support multiple models or workloads.
- Experience contributing to architecture and delivering technical initiatives involving multiple components or teams.
- Experience with distributed systems and large-scale machine learning workloads.
- Demonstrated interest in AI safety and Responsible AI, including building systems that support the safe and responsible development or deployment of AI capabilities.
- Demonstrated experience deploying and scaling machine learning models or pipelines in production.
- Software engineering, system design, and problem-solving skills.
- Experience building systems for one or more stages of the machine learning lifecycle, such as data processing, training, evaluation, or inference.
- Ability to independently deliver complex technical projects and collaborate effectively across science and engineering disciplines.
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.
Skills Required
- Bachelor's degree in Computer Science or a related technical field, plus 4 or more years of technical engineering experience with coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements.
- Pass the Microsoft Cloud Background Check upon hire or transfer and every two years.
- Master's or Doctorate degree in Computer Science or a related technical field focused on machine learning or related areas, plus 5 or more years of technical engineering experience, or equivalent experience.
- Experience building machine learning infrastructure or platforms supporting multiple models or workloads.
- Experience contributing to architecture and delivering technical initiatives involving multiple components or teams.
- Experience with distributed systems and large-scale machine learning workloads.
- Demonstrated interest in AI safety and Responsible AI, including systems supporting safe and responsible AI development or deployment.
- Experience deploying and scaling machine learning models or pipelines in production.
- Software engineering, system design, and problem-solving skills.
- Experience building systems for data processing, training, evaluation, or inference stages of the machine learning lifecycle.
- Ability to independently deliver complex technical projects and collaborate across science and engineering disciplines.
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
-
Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
-
Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
-
Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
Microsoft Insights
What We Do
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.
