Job Description
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 focus on real‑world impact.
- work end‑to‑end: from problem formulation and data analysis, through model development and experimentation, to production deployment and live flighting.
- 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:
- Bachelor's Degree in Computer Science, or Computer Engineering, or related field AND 4+ years related experience
- OR Master's Degree in Computer Science, or Computer Engineering, or related field AND 3+ years related experience
- OR Doctorate in Statistics, Econometrics, Computer Science, or Computer Engineering, or related field AND 1+ year(s) related experience
- OR equivalent experience.
Preferred Qualifications:
- Doctorate in Computer Science, or Computer Engineering, or related field AND 3+ years related experience
- 3+ years of experience applying AI solutions or LLMs to real‑world systems (RAG, ranking, classification, reasoning).
- Proven experience in distributed training, model optimization, and production ML infrastructure.
- Hands‑on experience developing and evaluating models on large‑scale, real‑world datasets.
- Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar).
- In depth nderstanding of experimentation methodologies, including offline metrics and online A/B testing.
- Ability to independently scope problems and deliver high‑quality solutions in ambiguous environments.
- Proven 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.
- 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 $119,800.00 - $234,700.00 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 $160,200.00 - $261,000.00 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.
