This role at Microsoft focuses on building and maintaining machine learning models for ad retrieval and quality prediction within the AI monetization team. The team is dedicated to optimizing personalized content and ads across Microsoft platforms, leveraging advanced techniques in machine learning and natural language processing. Candidates are expected to have a strong background in data analysis and experimentation, with a preference for those holding a PhD. The position is based in Redmond, Washington, and aims to tackle complex technical challenges in online advertising.

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience OR Master's Degree in the same fields AND 1+ year(s) related experience OR Doctorate in the same fields OR equivalent experience.
• 2+ years experience delivering, scaling, and maintaining highly successful and innovative machine learning products.
• 1+ year(s) experience creating publications such as patents or peer-reviewed academic papers.
• Demonstrated experience working with Large Language Models like GPT or BERT.
• In-depth knowledge of natural language processing techniques and concepts.

• Build and maintain production machine learning models for ad retrieval, quality prediction, and creative generation.
• Find insights and form hypotheses on web-scale data using various machine learning and data mining techniques.
• Design experiments and produce actionable conclusions from the resulting data.
• Craft and optimize prompts for effective performance of large language models.
• Wrangle large amounts of data using various tools and programming languages.

• 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.