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Microsoft Teams is the hub for modern collaboration—bringing together everything teams need to succeed, all within the Microsoft 365 ecosystem. It serves as the canvas that unifies your content, tools, people, and conversations in one seamless experience. As one of Microsoft’s most dynamic and impactful products, Teams is redefining the future of teamwork—and we’re just getting started.

Join us on this journey as we push the boundaries of what’s possible with Generative AI, Large Language Models (LLMs), and a world-class AI stack powering Teams Copilot and other cutting-edge AI experiences. You’ll be part of a team at the forefront of AI innovation, leveraging the latest in machine learning, deep learning, and natural language processing to shape the future of work.

Within the Messaging Services and AI teams, we’re evolving our machine learning platform to deliver intelligent, context-aware features while ensuring high performance, scalability, and efficiency. We’re looking for an experienced Principal Machine Learning Engineer to design, build, and optimize ML systems that power next-generation AI capabilities in Teams. This is a unique opportunity to work on large-scale applied AI, model deployment, and production-grade ML pipelines—all while collaborating with researchers and engineers across Microsoft.

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, develop, and deploy scalable machine learning models that enhance core collaboration and messaging experiences in Microsoft Teams.

+ Apply advanced techniques in deep learning, natural language processing, and generative AI to improve user experience and enable intelligent features.

+ Build and optimize ML pipelines for model training, evaluation, and deployment using Azure Machine Learning and other cloud-based services.

+ Prototype, experiment, and evaluate new ideas to deliver next-generation AI-powered features that redefine how teams communicate and collaborate.

+ Partner with research teams to bring cutting-edge ML innovations into production environments.

+ Collaborate with product engineering teams to integrate ML models into large-scale distributed systems, ensuring reliability and performance.

+ Establish best practices, frameworks, and reusable components for large-scale ML development across Microsoft and uphold the highest standards of availability, reliability, and scalability in ML systems—never compromising on engineering fundamentals.

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, C, C++, C#, Java, JavaScript, or Python

+ OR equivalent experience.

+ 3+ years of experience in applied machine learning, deep learning, or natural language processing.

+ 2+ years of hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow) and data processing pipelines.

+ 2+ years of experience deploying models to production in large-scale distributed systems or cloud environments (Azure, AWS, or GCP).

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.

Preferred Qualifications:

+ Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

+ OR equivalent experience.

+ 8+ years of technical engineering experience, including designing, training, and deploying ML models at scale.

+ Experience working with large language models (LLMs), generative AI, or conversational AI systems.

+ Familiarity with distributed computing frameworks (Kubernetes, Spark, Ray) and MLOps practices.

+ Solid track record of improving system performance, availability, and scalability.

+ Drive to automate, optimize, and innovate in ML workflows.

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $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

Microsoft will accept applications for the role until September 21, 2025.

Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .