The Augmented Learning and Reasoning (ALR) group in Microsoft Research utilizes large-scale interaction data to enhance our understanding of LFM-based AI systems and develop algorithmic innovations to improve their performance. This includes work on personalization, recommendations, prompt optimization, evaluation, data generation, fine-tuning, and alignment. We work closely with various Microsoft product teams that create and deploy copilots to drive cutting-edge research for large-scale AI systems using ML and AI methodologies.  

We are looking for researchers who have a strong interest in pushing the boundaries of learning and reasoning with foundation models and a proven ability to conduct impactful independent research. You will develop innovative machine learning techniques and shape/advance the research agenda of the team while collaborating widely across the organization. 

We are particularly interested in candidates who are passionate about (1) improving the performance of generative AI models, (2) enhancing user experiences in copilot systems, and (3) discovering simple, generalizable ideas that work well in practice and at scale. Candidates should have experience in one or more of the following areas: Foundation Models, Deep Learning, Reinforcement Learning, Multi-Objective Optimization, Natural Language Processing, Interactive Learning, Behavioral Modeling, Artificial Intelligence, Machine Learning, Search/Recommendation