Senior Applied Scientist

Microsoft • Redmond, WA

1d • $119,800 - $261,000

About The Position

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

The role leads high-impact projects from ideation through implementation, experimentation, and shipping, and contributes to the technical direction and career development of an applied science team. It combines scientific and engineering rigor, strategic execution, cross-organizational collaboration, and people management to improve Copilot Chat, Copilot Search, and BizChat. The scientist will also help set the direction for agentic search in Copilot Chat and share experimental results and learnings across the organization.

Microsoft describes its mission as empowering every person and organization to achieve more, and emphasizes growth mindset, innovation, collaboration, respect, integrity, accountability, and inclusion. The position requires passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter. The position will be open for at least five days, with applications accepted on an ongoing basis until filled. The typical U.S. base pay range is $119,800–$234,700 per year; the range for the San Francisco Bay Area and New York City metropolitan area is $160,200–$261,000 per year. Certain roles may be eligible for benefits and other compensation; the posting directs candidates to Microsoft’s careers site for additional benefits and pay information.

Requirements

• Bachelor's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field and 4+ years of related experience, or a master's degree in one of those fields and 3+ years of related experience, or a doctorate in one of those fields and 1+ year of related experience, 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.

Nice To Haves

• Master's degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field and 9+ years of related experience, or a doctorate in one of those fields and 6+ years of related experience, 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 methods, including offline metrics, A/B testing, and relevance judgments.

Responsibilities

• Lead end-to-end applied science projects, from ideation and design through implementation, experimentation, and shipping, to improve Copilot Chat, Copilot Search, and BizChat.
• Identify search and relevance gaps, formulate hypotheses, and deliver scalable solutions.
• Mentor and empower a team of applied scientists, guiding technical direction, project execution, day-to-day work, and career development; ensure scientific and engineering rigor and be accountable for team output and impact.
• Invent and apply machine learning, natural language processing, and information retrieval techniques to improve retrieval, ranking, query understanding, and semantic search at enterprise scale.
• Document experimental results and methodologies, publish internal learnings, and promote knowledge sharing across the organization.
• Partner with product and business stakeholders to align team work with priorities and translate ambiguous requirements into clear, data-driven, technically feasible directions.
• Collaborate with platform engineering teams, peer science organizations, and product managers across organizations and time zones to align 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