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About the Role

We are seeking a Senior Applied Scientist with deep expertise in modern retrieval technologies to shape the future of Microsoft 365 Copilot, focusing on Search, Chat, and Agent experiences. This role is within the Copilot and Agents Core (CACore) organization, which powers M365 Copilot by integrating generative AI with personalized search, retrieval, and recommendation systems. You will build state-of-the-art retrieval systems serving millions of enterprise users daily, partnering with engineering, product, and platform teams to innovate and evaluate retrieval and ranking technologies. This high-impact role involves influencing technical strategy, shaping retrieval architecture, and collaborating across Microsoft Research, Azure AI, and product groups to deliver AI-powered experiences.

Responsibilities

Design and run experiments, define offline and online evaluation metrics, and develop scalable retrieval pipelines and models for enterprise-scale search systems.
Advance semantic retrieval using late-interaction architectures such as ColBERT.
Fine-tune dense retrieval and embedding models.
Develop modern lexical retrieval approaches such as SPLADE.
Build hybrid retrieval systems combining dense + sparse retrieval.
Improve query understanding and representation learning.
Optimize multi-stage ranking and retrieval.
Implement retrieval-augmented generation (RAG).
Develop personalization and contextual ranking strategies.
Build knowledge retrieval for agentic AI systems.
Create reinforcement learning and reasoning-aware retrieval systems.
Develop LLM-integrated retrieval architectures.
Apply best practices in Responsible AI, Privacy-Preserving ML, and scalability for production-grade enterprise 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.
Collaborate with Microsoft Research, Azure AI platform teams, and product organizations to integrate cutting-edge retrieval and ranking advances into large-scale production systems.
Understand user retrieval pain points and enterprise grounding challenges, and develop solutions that improve relevance, answer quality, freshness, and personalization.
Provide technical leadership and mentorship to scientists and engineers working on retrieval, ranking, and recommendation systems.
Establish best practices and contribute to the broader retrieval science strategy across CACore.
Establish and evolve evaluation frameworks and success metrics for retrieval quality, grounding relevance, ranking effectiveness, and downstream Copilot quality metrics.
Stay current with the latest advances in retrieval and ranking research, including semantic retrieval, sparse retrieval, RAG systems, and LLM-grounded search.
Publish research at top-tier venues such as SIGIR, RecSys, WSDM, KDD, ACL, and EMNLP.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience OR equivalent experience.
Ability to meet Microsoft, customer, and/or government security screening requirements.
Must pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Skills

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
ML systems in Python
Modern ML frameworks such as PyTorch
Evaluating retrieval quality using offline metrics and/or online experimentation
Retrieval systems for RAG or agentic AI architectures
Retrieval systems integrated with LLM-based products
Enterprise search
Personalization and recommendation systems
Optimizing retrieval latency, scalability, and serving infrastructure
Reinforcement learning or retrieval-aware reasoning systems

Location

United Kingdom

Work Type

Full-time

Experience Level

Senior
4+ years related experience
3+ years related experience
1+ year(s) related experience

Education Level

Bachelor's Degree
Master's Degree
Doctorate

Salary/Compensations

£ 74,700.00 - £ 122,600.00 per year

Benefits

Certain roles may be eligible for benefits and other compensation.

About the Company

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.

Equal Opportunity

Microsoft is an equal opportunity employer.
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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.