Principal Machine Learning Engineer - RAI
About The Position
The Principal Machine Learning Engineer will design, build, deploy, and scale production machine learning systems. This deeply technical, hands-on role focuses on transforming machine learning models and research innovations into reliable product capabilities across the machine learning lifecycle, including data processing, model training, evaluation, inference, and production operation. The engineer will partner closely with applied scientists and software engineers to solve complex problems involving models, data, infrastructure, and services. The role includes building critical system components while driving architecture and technical direction across broader initiatives. The engineer will develop reusable capabilities for multiple models and workloads, balance model quality with scalability, reliability, performance, and cost, and help raise engineering standards across the team. The position is 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.
Requirements
- Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years.
Nice To Haves
- Master's or Doctorate degree in Computer Science or a related technical field, with a focus on machine learning or related areas, and 7+ years of technical engineering experience, or equivalent experience.
- Experience building machine learning infrastructure or platforms that support multiple models, teams, or workloads.
- Experience driving architecture across complex, cross-team engineering initiatives.
- 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 and pipelines in production.
- Experience with machine learning systems, distributed systems, software architecture, and system design.
- Proven ability to build and operate systems that support large-scale machine learning workloads.
- Ability to solve technically ambiguous problems and personally implement critical systems while influencing broader technical direction.
Responsibilities
- Design and build large-scale systems for machine learning training, evaluation, inference, and production operation.
- Transform machine learning models and research innovations into reliable, scalable product capabilities.
- Develop reusable infrastructure, services, and components that support multiple models and workloads.
- Solve complex engineering problems involving scalability, performance, reliability, and efficiency.
- Partner with applied scientists and software engineers to integrate modeling advances into production systems.
- Drive architectural decisions while remaining hands-on in the design and implementation of critical components.
- Incorporate security, privacy, safety, and Responsible AI considerations throughout system design and development.
- Provide technical direction and mentorship that raises the engineering bar across the team.
Benefits
- Certain roles may be eligible for benefits and other compensation; additional benefits and pay information is available through Microsoft Careers.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
