As a **Principal Applied Scientist** , you will define the future of AI in Microsoft Teams—leading the design, development, and deployment of intelligent features that transform the way people collaborate worldwide. Beyond delivering groundbreaking AI experiences, you will set the scientific vision for the team, mentor talent, and ensure our solutions exemplify rigor, responsibility, and ethical standards. In this role, you will operate at the intersection of research and product—applying state-of-the-art techniques to address real-world challenges at global scale. You will collaborate closely with engineering and product teams to translate the latest advances in LLMs into reliable, high-impact user experiences. 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** + Research, design, and prototype methods to leverage LLMs for product scenarios such as text understanding, summarization, dialogue, translation, content generation, and reasoning. + Fine-tune, adapt, and optimize pre-trained LLMs for domain-specific tasks while balancing model performance, efficiency, and cost. + Develop scalable pipelines for data collection, cleaning, augmentation, and evaluation. + Collaborate with product and engineering teams to translate applied research into production-quality features. + Define and track key performance metrics for LLM-based features, including accuracy, latency, robustness, and user satisfaction. + Stay current with advances in generative AI, multimodal models, and applied ML techniques, and bring forward innovative ideas to improve our products. + Publish technical insights internally (and externally where appropriate) to advance organizational knowledge and thought leadership. **Qualifications** **Required Qualifications:** + Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) + OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) + OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) + OR equivalent experience. + 5+ years of experience in applied machine learning, natural language processing (NLP), or related domains. + Strong knowledge of modern NLP methods, particularly transformers, LLMs, and transfer learning. + Hands-on experience with at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX). + Proficiency in Python and familiarity with ML tooling, experimentation, and evaluation frameworks. + Experience with data preprocessing, feature engineering, and large-scale training/inference. + Strong analytical and problem-solving skills, with ability to bridge research and product needs. **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:** + MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field, or equivalent industry experience. + 7+ years of experience in applied science roles focused on AI/ML or NLP, with a track record of technical excellence and innovation. + Experience fine-tuning or instruction-tuning large foundation models. + Knowledge of prompt engineering, retrieval-augmented generation (RAG), or multi-agent LLM systems. + Familiarity with distributed training, model optimization, and deployment in production systems. + Track record of published work in ML/NLP conferences or journals. + Experience working in cross-functional teams, shipping AI-powered features to users. 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) .