Applied Scientist II (Bing Places)

Applied Scientist II (Bing Places) | Microsoft Careers Skip to main content Microsoft Careers Careers Careers Search Search jobs Sign in Single PositionView All JobsApplied Scientist II (Bing Places)United States, Washington, Redmond +1 moreApply nowAdd to cartFind out how well you match with this jobUpload your resumeJob descriptionCompany and benefitsJob number200034701Date postedJul 21, 2026Work site4 days / week in-officeTravelLess than 25%ProfessionResearch, Applied, & Data SciencesDisciplineApplied SciencesRole typeIndividual ContributorEmployment typeFull-TimeOverviewThe Bing Places team is building intelligence that powers local search experiences used by millions of people every day. We are looking for Applied Scientists to help design, build, and ship advanced AI and machine learning solutions—spanning large language models (LLMs), retrieval augmented generation (RAG), learning‑to‑ranking, and entity understanding—to deliver high‑quality, trustworthy local search experiences at scale.As an Applied Scientist on Bing Places,You will work on challenging problems that require deep technical expertise and a strong focus on real‑world impact.You will work end‑to‑end: from problem formulation and data analysis, through model development and experimentation, to production deployment and live flighting.You will collaborate closely with engineering and product partners to develop, experiment with, and ship models that operate at Microsoft scale, while contributing to the broader scientific community through publications and patentsResponsibilitiesFormulate complex product and engineering problems as machine learning and AI tasks, and drive them from concept through productionDesign, implement, and evaluate ML‑ and LLM‑based models that improve Bing Places quality, relevance, and coverageConduct rigorous data analysis to understand system behavior, identify opportunities, and define success metricsPrototype new modeling approaches and iterate quickly based on offline evaluation and online experimentationOwn experimentation pipelines, including offline validation and large‑scale online A/B flightingPartner closely with engineers to integrate models into production systems and ensure long‑term reliability and performanceDrive technical direction within your problem space and influence broader modeling and platform decisionsDocument and communicate results through technical design reviews, papers, and patent filingsQualificationsRequired Qualifications: 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.Preferred Qualifications: Master’s degree or PhD in a relevant technical field4+ years of experience applying AI solutions or LLMs to real‑world systems (RAG, ranking, classification, reasoning)Proven expertise in machine learning, statistical methods, and data‑driven problem solvingHands‑on experience developing and evaluating models on large‑scale, real‑world datasetsProficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar)Understanding of experimentation methodologies, including offline metrics and online A/B testingAbility to independently scope problems and deliver high‑quality solutions in ambiguous environmentsStrong collaboration skills and experience working with engineering and product partnersAbility to clearly communicate technical concepts and trade‑offs to both technical and...