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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 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 AI areas into reliable, high-impact user experiences.
Job Responsibility:
Research, design, and prototype methods to leverage AI for product scenarios such as text understanding, summarization, dialogue, translation, content generation, and reasoning
Fine-tune, adapt, and optimize pre-trained AI for domain-specific tasks while balancing 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 AI features, including accuracy, latency, robustness, and user satisfaction
Stay current with advances in generative AI, multimodal, 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
Requirements:
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
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
OR equivalent experience
MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field, or equivalent industry experience
5+ years of experience in applied machine learning, natural language processing (NLP), or related domains
Strong knowledge of modern NLP methods, particularly transformers 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
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
Nice to have:
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
OR equivalent 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
Knowledge of prompt engineering, retrieval-augmented generation (RAG), or multi-agent systems
Familiarity with distributed training, 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