Applied Scientist II

Microsoft•Redmond, WA

5d•$102,100 - $219,200•Hybrid

About The Position

Do you want to be part of a team that delivers innovative products and machine learning solutions to hundreds of millions of users across Microsoft every month? The Copilot Agent & Search Quality team is at the forefront of the core Copilot experiences across Microsoft products, including Copilot Chat and Search, helping users find the right information in their organization and accelerating their productivity. As an Applied Scientist II on the Microsoft Search Relevance team, you will work alongside other scientists to solve challenging problems that delight Copilot Search and Chat users. Examples include adapting state-of-the-art vector search algorithms to the enterprise domain, and applying advanced ML to improve the retrieval quality of business-critical information by jointly optimizing query understanding and the retrieval algorithm. You will also partner closely with our platform team to accelerate the evaluation of retrieval algorithms at scale. This position is based in Redmond, Washington and requires the employee be in the office a minimum of 3 days per week. 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.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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.
1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
Experience applying machine learning, NLP, or information retrieval techniques to search or recommendation problems.
Experience using data analysis and offline/online evaluation to diagnose model behavior and improve product quality.
Applied ML engineering experience using Python and modern ML frameworks such as PyTorch.
Hands-on experience with dense/vector retrieval and text embeddings, including bi-encoders, approximate nearest-neighbor search, contrastive training, or hard-negative training.
Familiarity with information retrieval fundamentals and retrieval evaluation, including metrics such as recall@k and nDCG, offline evaluation pipelines, and interpretation of A/B test results.
Experience fine-tuning or adapting transformer or large language models for a specific domain, including domain adaptation, distillation, parameter-efficient fine-tuning, and curation of clean in-domain training data.
Solid applied ML engineering skills in Python and PyTorch, with experience running large-scale training and evaluation jobs on cloud or GPU clusters.

Responsibilities

Research and evaluate tools, technologies, and methods from the community that can improve the quality, performance, or efficiency of M365 Copilot Chat and Search, and apply them to deliver business impact.
Build deep knowledge of the M365 Copilot Search service while staying current with industry trends and advances in applied ML (machine learning). Consult with engineers and product teams to apply advanced concepts to search quality improvements.
Use data to identify opportunities to apply state-of-the-art algorithms that improve M365 Copilot search quality. Apply statistical analysis to evaluate the behavior of deployed models, validate assumptions about evaluation results, and communicate insights to the team.
Develop expertise in search relevance, NLP (natural language processing), and data-driven analysis, along with the relevant research literature and techniques. Use this understanding to identify, adapt, or create research-backed solutions—novel, data-driven, scalable, and extensible—that improve M365 Copilot Chat and Search quality.
Build collaborative relationships with product and business groups across Microsoft, contributing expertise and technology that create business impact. This may include authoring white papers, developing and maintaining internal tools and services, and publishing research.