Senior Applied Scientist

Microsoft • Redmond, WA

23h • $119,800 - $234,700

About The Position

The CASQ (Copilot, Agents, Search Quality) Search Relevance team develops search quality across Microsoft products. It supports relevance in Copilot Search and the core retrieval layer for the RAG architecture powering BizChat, while also maintaining search quality in Outlook, Teams, and SharePoint. The Senior Applied Scientist will deliver applied machine learning and information retrieval solutions for enterprise-scale search, including dense retrieval, hybrid search, multilingual LLMs, RAG, transformer-based reranking, and agentic search.

The role combines technical leadership, strategic execution, and people management. It involves leading projects from ideation through implementation, experimentation, and launch; guiding and developing applied scientists; advancing retrieval, ranking, query understanding, and semantic search; and aligning scientific work with product priorities. The scientist will collaborate with engineering, science, and product teams across organizations and time zones to improve Copilot Chat, Copilot Search, and BizChat experiences.

Requirements

• Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field, plus 4+ years of related experience; or a master's degree in one of these fields plus 3+ years; or a doctorate in one of these fields plus 1+ year; or equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
• Preferred: Master's degree in a listed or related field plus 9+ years of related experience; or doctorate in a listed or related field plus 6+ years; or equivalent experience.
• 5+ years of experience taking applied science projects from ideation to production in high-scale environments such as search, recommendation, or conversational AI.
• 5+ years of experience analyzing data at scale, including logs, telemetry, and large datasets to identify behavioral patterns, build evaluation datasets, and derive insights.
• 6+ years of experience creating publications, such as patents, libraries, or peer-reviewed academic papers.
• 2+ years of experience presenting as an invited speaker at conferences or other events in the external research or industry community.
• 5+ years of experience conducting research as part of an academic or industry research program.
• 5+ years of experience developing and deploying live production systems as part of a product team.
• 5+ years of experience developing and deploying products or systems at multiple points in the product cycle, from ideation to shipping.
• Experience with search and ranking systems, semantic retrieval, and information retrieval at scale.
• Applied experience with state-of-the-art sparse and dense retrieval and ranking techniques.
• Experience with RAG architectures using LLMs such as OpenAI GPT, T5, or Llama.
• Experience fine-tuning or prompt engineering large-scale language models for query rewriting, summarization, and document reranking.
• Familiarity with hybrid search strategies, learning-to-rank frameworks, and information retrieval evaluation methodologies, including offline metrics, A/B testing, and relevance judgments.

Responsibilities

• Lead end-to-end applied science projects, from identifying search and relevance gaps and developing hypotheses through implementation, experimentation, and launch.
• Mentor and empower a team of applied scientists, guiding technical direction, project execution, scientific and engineering rigor, and career development.
• Invent and apply machine learning, natural language processing, and information retrieval techniques for enterprise-scale retrieval, ranking, query understanding, and semantic search.
• Document experimental results and methodology, publish internal learnings, and promote knowledge sharing.
• Partner with product and business stakeholders to translate business goals and ambiguous product requirements into clear, data-driven, technically feasible scientific strategies.
• Collaborate with platform engineering teams, peer science organizations, and product managers across organizations and time zones to coordinate work, resolve dependencies, and unblock progress.
• Set vision and direction for agentic search in Copilot Chat using state-of-the-art methods and data-driven analysis.
• Embody Microsoft's culture and values.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior