Join our innovative Copilot Search & Agents team as an Applied Scientist II, specializing in Machine Learning. You’ll contribute to building the next generation of search technology, empowering millions globally with relevant information experiences. This role offers a unique opportunity to work on core search stacks and shape the future of enterprise search powered by advanced AI.

We are a passionate team with a long history in machine learning, dedicated to solving real-world problems. You will be part of a dynamic and collaborative environment, pushing the boundaries of state-of-the-art SLMs, Deep Neural Nets, Embedding Models, and classical Gradient Boosted Tree models.

Advance scientific understanding by designing and executing experiments, validating metrics, and developing ML pipelines and models. Focus areas include encoder-decoder and cross-encoder models, as well as language models for intent understanding and semantic search optimization.

Drive product innovation by partnering with Engineering, PM, and Design to translate product visions into scalable architectures. Foster collaboration across Microsoft teams, including Research and AI platform groups, to integrate cutting-edge AI into practical applications. Champion customer impact by understanding user pain points and driving meaningful improvements.

We seek candidates with deep expertise in applied AI and a proven ability to deliver ML models at scale. Essential qualifications include a Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, combined with at least 2 years of relevant experience. Alternatively, a Master's degree with 1+ year of experience, or a Doctorate in a relevant field, or equivalent experience is acceptable.

Preferred qualifications include a Bachelor's degree with 5+ years of experience, or a Master's degree with 2+ years of experience, or a Doctorate in a relevant field. Proficiency in Python coding for at least 3 years is also highly desirable. Experience in statistics, predictive analytics, and research is crucial for success in this role.