Principal Machine Learning Engineer

Microsoft hybrid • Redmondfull_time
OneDrive & SharePoint (ODSP) Applied Science’s mission is to invent the AI‑native knowledge substrate for Microsoft 365—turning the world’s largest enterprise content platform (ODSP) into a foundation for specialized, enterprise‑ready, planet‑scale AI and agents. We’re building durable memory and statefulness for AI, advancing trustworthy solutions for LLMs to interact with data, and optimizing end‑to‑end systems for quality, cost, and latency at massive global scale.


We are seeking a passionate, creative, and analytical individual contributor with expertise in training or fine-tuning large language models, including both text and multimodal systems, reinforcement learning, agentic AI architectures, and inference optimization. As a Principal Machine Learning Engineer, you will collaborate with a team of passionate engineers and applied scientists, driving ideas to impactful results in a fast-paced environment. You will work on designing, building, and deploying large-scale machine learning and agentic systems, with an emphasis on production-grade solutions involving data pipelines, large-scale training, model serving, and performance optimization. You are experienced in machine learning engineering from ideation and algorithm selection to architecture and implementation, to deployment and continuous improvement.

 

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.