About the job
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.
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
Minimum
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.
Preferred
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.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 (e.g., PyTorch, TensorFlow, JAX, or similar).Solid understanding of experimentation methodologies, including offline metrics and online A/B testing.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 (RAG, ranking, classification, reasoning).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.