Senior Applied Scientist (Bing Places)

## About the role * 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. * 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. ## Requirements * 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. * 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.