The Bing Places team is building intelligence that powers local search experiences used by millions of people every day. We are looking for a Senior Applied Scientist 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 a Senior Applied Scientist on Bing Places, you will work on challenging problems that require deep technical expertise and a solid 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.
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.
Responsibilities:
Formulate complex product and engineering problems as machine learning and AI tasks, and drive them from concept through production.
Design, implement, and evaluate ML-and LLM-based models that improve Bing Places quality, relevance, and coverage.
Conduct rigorous data analysis to understand system behavior, identify opportunities, and define success metrics.
Prototype new modeling approaches and iterate quickly based on offline evaluation and online experimentation.
Own experimentation pipelines, including offline validation and large-scale online A/B flighting.
Partner closely with engineers to integrate models into production systems and ensure long-term reliability and performance.
Drive technical direction within your problem space and influence broader modeling and platform decisions.
Document and communicate results through technical design reviews, papers, and patent filings.
Qualifications:
Required qualifications include a 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 a related field and 3+ years of related experience, or a doctorate in a related field and 1+ year of related experience.
Preferred qualifications include a master’s degree in a related field and 6+ years of related experience, or a doctorate in a related field and 3+ years of related experience.
Solid foundation in machine learning, statistical methods, and data-driven problem-solving.
Hands-on experience developing and evaluating models on large-scale, real-world datasets.
Proficiency in Python and experience with modern ML frameworks.
Solid understanding of experimentation methodologies.
Ability to independently scope problems and deliver high-quality solutions in ambiguous environments.
Solid collaboration skills and experience working with engineering and product partners.
Ability to clearly communicate technical concepts and trade-offs to both technical and non-technical audiences.
4+ years of experience applying AI solutions or LLMs to real-world systems.
Background in search, information retrieval, knowledge graphs, or local/entity understanding.
Experience shipping models into large-scale production systems with real user impact.
Track record of publications or granted/pending patents.
Familiarity with distributed training, model optimization, and production ML infrastructure.
Comfort operating across the full lifecycle,from research and prototyping to production and live operations.
#MicrosoftAI Applied Sciences IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 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 $158,400 – $258,000 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
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