Senior Applied Scientist

Job Description Senior Applied Scientist – LLM at Microsoft. We are building the Intelligent Conversation and Communications Cloud (IC3). We power Microsoft’s first–party real‑time conversation products, notably Skype and Teams, with reliable high‑quality audio and video calling, meetings, and chat services that work every time from anywhere on any device. IC3 enables customers to do more by making conversations more intelligent, surfacing useful information in real time, and taking actions on the customers’ behalf during the conversation. We are also building a new real‑time communication platform from the ground up—an agent‑first, AI‑ready communications platform that breaks the mold of traditional conference calls and advances standards for agentic communications. As a Senior Data & Applied Scientist, you will play a pivotal role in transforming traditional media applications with AI power. You’ll develop scalable algorithms and machine learning pipelines, use large language models to drive innovation with real‑time media, and produce grounding data for intelligence processing. This unique opportunity crosses platform engineering and applied science, shaping the future of AI‑powered productivity. Responsibilities Drive data exploration and analysis by collecting initial datasets, selecting appropriate analytical techniques, and applying foundational statistical methods to extract insights. Leverage generative AI and agentic orchestration to build intelligent systems that power multi‑modal media processing. Design and implement advanced LLM‑based architectures and agentic systems for real‑world product scenarios. Apply and adapt research ideas to solve practical challenges in reasoning, planning, memory, and alignment. Collaborate with cross‑functional teams—including product, engineering, and research—to align efforts and deliver high‑impact solutions. Champion customer‑centric solutions by understanding business goals, identifying growth opportunities, and managing expectations throughout the project lifecycle. Qualifications Required Qualifications Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience. OR Master’s Degree in the same fields AND 3+ years related experience. OR Doctorate in the same fields AND 1+ year(s) related experience. OR equivalent experience. 4+ years of experience in applied machine learning, focusing on LLMs, agent systems, or reinforcement learning. Preferred Qualifications Hands‑on experience with model training pipelines using PyTorch, TensorFlow, JAX, or similar frameworks. Familiarity with distributed training, prompt engineering, evaluation strategies, and model deployment best practices. Coding and debugging skills, and comfort working in cross‑functional, agile environments. Other Requirements Ability to meet Microsoft, customer, and/or government security screening requirements. This includes passing the Microsoft Cloud background check upon hire/transfer and every two years thereafter. Compensation Typical base pay range in Canada: CAD $114,400 – $203,900 per year. Additional pay information: https://careers.microsoft.com/v2/global/en/canada-pay-information.html Application Deadline Microsoft will accept applications for the role until November 3rd, 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. #J-18808-Ljbffr