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About the Role
We are seeking a Principal 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, powering M365 Copilot by integrating generative AI with personalized search, retrieval, and recommendation systems. You will work in a fast-paced, collaborative environment building state-of-the-art retrieval systems for millions of enterprise users daily. You will partner with engineering, product, and platform teams to innovate, design, and evaluate retrieval and ranking technologies that enhance grounding quality, relevance, personalization, and reasoning capabilities across Microsoft 365 Copilot experiences. 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.
- Focus on semantic retrieval using late-interaction architectures such as ColBERT.
- Focus on dense retrieval and embedding model fine tuning.
- Focus on modern lexical retrieval approaches such as SPLADE.
- Focus on hybrid retrieval systems combining dense + sparse retrieval.
- Focus on query understanding and representation learning.
- Focus on multi-stage ranking and retrieval optimization.
- Focus on retrieval-augmented generation (RAG).
- Focus on personalization and contextual ranking.
- Focus on knowledge retrieval for agentic AI systems.
- Focus on reinforcement learning and reasoning-aware retrieval systems.
- Focus on 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.
- Help 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 updated with the latest advances in retrieval and ranking research, including semantic retrieval, sparse retrieval, RAG systems, and LLM-grounded search.
- Publishing at top-tier venues such as SIGIR, RecSys, WSDM, KDD, ACL, and EMNLP is encouraged.
Requirements
- Bachelor's, Master's, or Doctorate Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND related experience (e.g., statistics predictive analytics, research), 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
- Recommendation systems
- Optimizing retrieval latency, scalability, and serving infrastructure
- Reinforcement learning
- Retrieval-aware reasoning systems
Location
- United Kingdom
Work Type
- Full-time
Experience Level
- Principal Applied Scientist
- Applied Sciences IC4
- Applied Sciences IC5
Education Level
- Bachelor's Degree
- Master's Degree
- Doctorate Degree
Salary/Compensations
- £ 74,700.00 - £ 122,600.00 per year (IC4)
- £ 93,500.00 - £ 161,800.00 per year (IC5)
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.