Responsibilities
- Define technical direction for cloud infrastructure and machine learning platforms across multiple engineering teams.
- Design and review distributed systems that support model training, model inference, data processing, and platform services.
- Work with partner teams to align architecture, reliability, security, scalability, and operational requirements.
- Improve platform efficiency, including compute utilization, resource management, and service performance.
- Support Machine Learning Operations (MLOps) practices for model development, deployment, monitoring, and lifecycle management.
- Provide technical guidance for Kubernetes-based platforms and Artificial Intelligence (AI) workloads running in production environments.
- Contribute to long-term platform planning, technical standards, and engineering best practices across the organization.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, Go, 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 thereafter.
- Master's Degree in Computer Science, Computer Engineering, or a related technical field AND 8+ years of technical engineering experience developing software in Go, C, C++, C#, Java, JavaScript, or Python
- OR Bachelor's Degree in Computer Science, Computer Engineering, or a related technical field AND 12+ years of technical engineering experience developing software in Go, C, C++, C#, Java, JavaScript, or Python
- OR equivalent practical experience.
- Deep experience with Kubernetes, containers, cloud platforms, networking, storage systems, site reliability engineering, and large-scale distributed systems.
- Experience designing and operating machine learning platforms, large-scale model training environments, graphics processing unit infrastructure, distributed batch scheduling systems, machine learning operations frameworks, KubeRay, and Kueue.
- Strong understanding of modern large language model and foundation model ecosystems, including training, inference, model serving, and observability.
- Experience building and scaling enterprise artificial intelligence infrastructure and platforms that support production workloads.
- Demonstrated ability to lead architecture decisions and drive technical strategy across cross-functional engineering teams.
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:
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, or equivalent experience
- 6+ years of technical engineering experience with coding in Go, C, C++, C#, Java, JavaScript, Python, or similar languages
- Ability to pass the Microsoft Cloud Background Check and meet applicable security screening requirements
- Master’s degree in Computer Science, Computer Engineering, or a related technical field and 8+ years of technical engineering experience, or bachelor’s degree and 12+ years of experience, or equivalent practical experience
- Deep experience with Kubernetes, containers, cloud platforms, networking, storage systems, site reliability engineering, and large-scale distributed systems
- Experience designing and operating machine learning platforms, large-scale model training environments, GPU infrastructure, distributed batch scheduling systems, MLOps frameworks, KubeRay, and Kueue
- Understanding of large language model and foundation model ecosystems, including training, inference, model serving, and observability
- Experience building and scaling enterprise AI infrastructure supporting production workloads
- Ability to lead architecture decisions and drive technical strategy across cross-functional engineering teams
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.
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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.
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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.
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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.
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