Applied Scientist

Microsoft•Redmond, WA

10h•Hybrid

About The Position

Core Search and AI team (Bing) is looking for people who want to build the next generation of search using advanced AI technologies, especially large language models, at scale. We are responsible for the largest machine learning models at Microsoft by volume and take pride in being the first in the world to solve many practical AI at Scale challenges. Our work spans a very large scope of scenarios including delivering high quality search results from a massive document corpus, query and document understanding, retrieval and reranking model for search results optimization, as well as AI search grounding, etc. We are seeking a highly motivated and experienced Senior Applied Scientist with solid machine learning expertise and can adopt state-of-art AI technologies to improve the relevance for the next generation of search. As a team, we leverage the diverse backgrounds and experiences of passionate engineers, scientists, and program managers to help us realize our goal of making the world smarter and more productive. We believe great products are built by inclusive teams of customer-obsessed individuals who trust each other and work together closely. We collaborate regularly across the company to find technological breakthroughs from groups like Microsoft Research to infusing AI into the rest of Microsoft products like Office and Azure. 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. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ 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.
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

Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
5+ years of experience coding in Python, C++, C#, C or Java.
3+ year of industry experience applying Machine Learning techniques.

Responsibilities

You will master one or more subareas and build expertise across a broad research landscape, including advanced research methodologies and applied techniques. You’ll develop deep knowledge of a service, platform, or domain, and identify product opportunities by sharing emerging industry trends and applied technologies.
You will review business requirements and incorporate research insights to meet strategic goals. You’ll provide direction on the types of data needed to solve complex problems and apply deep subject‑matter expertise to drive measurable business impact.
You will support the onboarding of junior team members and help develop academic collaborators into effective contributors within multidisciplinary teams. You’ll identify promising research talent, engage with the academic community, and strengthen Microsoft’s long‑term recruiting pipeline.
You will document ongoing work, experimental results, and research findings to promote transparency and innovation. You’ll also apply your understanding of fairness and bias to help shape ethics and privacy policies related to research processes and data collection.
You will advance LLM post‑training and alignment techniques by designing, implementing, and evaluating novel methods that improve reasoning quality, safety, controllability, and factual grounding across large‑scale models.
You will develop next‑generation search capabilities by building and optimizing retrieval, ranking, and relevance systems that integrate deeply with LLM‑powered experiences.
You will architect and refine RAG pipelines that enhance retrieval fidelity, reduce hallucinations, and deliver more context‑aware, user‑aligned responses in production environments.
You will translate research into production by running experiments, analyzing results, and collaborating with engineering partners to deploy scalable, reliable model improvements.
You will drive scientific rigor through hypothesis‑driven experimentation, reproducible methodologies, and clear documentation of findings, insights, and model behaviors.
You will collaborate across disciplines—including research, engineering, product, and design—to shape long‑term strategy for search, alignment, and retrieval‑augmented systems.
You will monitor and evaluate model performance using quantitative metrics, qualitative assessments, and user‑centric evaluation frameworks to ensure continuous improvement.
You will contribute to a culture of innovation by sharing learnings, mentoring peers, and participating in internal research discussions, reviews, and technical deep dives.