About the job
We are looking for a Senior Applied Scientist with deep expertise in modern retrieval technologies to help shape the future of Microsoft 365 Copilot, with a focus on Search, Chat and Agent experiences. This role sits within the Copilot and Agents Core (CACore) organization, which powers the intelligence behind M365 Copilot by combining cutting-edge advances in generative AI with personalized search, retrieval and recommendation systems. As a Senior Applied Scientist in CACore, you will work in an exciting and fast-paced, collaborative environment focused on building state-of-the-art retrieval systems that serve millions of enterprise users daily.
Responsibilities
Design and run experiments, define offline and online evaluation metrics, and develop scalable retrieval pipelines and models for enterprise-scale search systems.
Partner with Engineering, PM and Design to translate product requirements and research advances into scalable and reliable retrieval infrastructure supporting Copilot Search, Chat and Agent experiences.
Work closely with Microsoft Research, Azure AI platform teams and product organizations to bring cutting-edge retrieval and ranking advances into large-scale production systems.
Deeply understand user retrieval pain points and enterprise grounding challenges, and develop solutions that materially improve relevance, answer quality, freshness and personalization.
Provide technical leadership and mentorship to scientists and engineers working on retrieval, ranking and recommendation systems.
Establish and evolve evaluation frameworks and success metrics for retrieval quality, grounding relevance, ranking effectiveness and downstream Copilot quality metrics.
Keep up with the latest advances in retrieval and ranking research, including developments in semantic retrieval, sparse retrieval, RAG systems and LLM-grounded search.
Qualifications
Minimum
Bachelor'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 Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
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
Strong hands-on experience developing retrieval or ranking systems at production scale.
Demonstrated expertise in one or more of the following: Semantic retrieval; Dense retrieval systems; Embedding model training or fine tuning; SPLADE or sparse retrieval methods; Hybrid retrieval architectures; Ranking systems for search or recommendation; Large-scale information retrieval systems.
Experience developing ML systems in Python and modern ML frameworks such as PyTorch.
Experience evaluating retrieval quality using offline metrics and/or online experimentation.
Experience developing retrieval systems for RAG or agentic AI architectures.
Publications in top-tier conferences such as SIGIR, RecSys, KDD, WWW, WSDM, ACL or EMNLP.
Experience shipping retrieval systems integrated with LLM-based products.
Familiarity with enterprise search, personalization and recommendation systems.
Experience optimizing retrieval latency, scalability and serving infrastructure.
Experience with reinforcement learning or retrieval-aware reasoning systems.