The Bing Places team is seeking Applied Scientists to develop advanced AI and machine learning solutions that enhance local search experiences. This role involves working on large language models, retrieval augmented generation, and entity understanding to deliver high-quality results at scale. The position requires collaboration with engineering and product teams to ensure successful model deployment and experimentation. Candidates will also contribute to the scientific community through publications and patents.

• Bachelor's Degree in a relevant field and 2+ years of related experience, or a Master's Degree with 1+ year of experience, or a Doctorate in a relevant field.
• Master’s degree or PhD in a relevant technical field is preferred.
• 4+ years of experience applying AI solutions or LLMs to real-world systems.
• Proven expertise in machine learning and statistical methods.
• Hands-on experience developing and evaluating models on large-scale datasets.
• Proficiency in Python and experience with modern ML frameworks.
• Understanding of experimentation methodologies, including offline metrics and online A/B testing.
• Strong collaboration skills and experience working with engineering and product partners.

• Formulate complex product and engineering problems as machine learning and AI tasks.
• Design, implement, and evaluate ML- and LLM-based models to improve Bing Places quality.
• Conduct rigorous data analysis to understand system behavior and define success metrics.
• Prototype new modeling approaches and iterate based on evaluation and experimentation.
• Own experimentation pipelines, including offline validation and large-scale online A/B flighting.
• Partner closely with engineers to integrate models into production systems.
• Drive technical direction within your problem space and influence broader decisions.
• Document and communicate results through technical design reviews and publications.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.