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Job Details
Posted date: May 11, 2026
Category: Applied Sciences
Location: Redmond, WA
Estimated salary: $158,000
Range: $100,600 - $215,400
Employment type: Full-Time
Work location type: 4 days / week in-office
Role: Individual Contributor
Description
OverviewThe 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 patents
Bing Location Understanding and Geocoding team - (Redmond, WA)
The Bing Location Understanding (BLU) and Bing Geocoding (BingGC) teams build the core intelligence that powers location interpretation, address understanding, and geospatial reasoning across Bing, Maps, and downstream Microsoft experiences. Our systems operate at global scale and combine machine learning, natural language understanding, ranking, and large‑scale data processing to deliver high‑quality results in real time.
Responsibilities
Formulate 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 filings
Qualifications
Required 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 non‑technical audiences
Background in search, information retrieval, knowledge graphs, or local/entity understandingTrack record of publications or granted/pending patentsFamiliarity with distributed training, model optimization, and production ML infrastructureComfort operating across the full lifecycle—from research and prototyping to production and live operations
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $131,400 - $215,400 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.