Senior Applied Scientist (Bing Places)

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.

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 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.
• 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.

The typical base pay range for this role across the U.S. is USD $119,800.00 – $234,700.00 per year.