Mountain View, United States; Redmond, United States
Full job description
Microsoft Monetization is seeking a Principal Applied Scientist and Technical Lead to drive the science vision, technical strategy, and execution for AI-powered relevance, intent understanding, personalization, recommendation, and agent-driven commerce experiences. The role involves leading multiple science areas, influencing architecture, research investments, model roadmaps, and execution strategies, while being hands-on in machine learning innovation. Responsibilities include leading AI initiatives across Copilot, Shopping, and Ads, driving innovation in ML technologies such as LLMs and multimodal AI, defining science roadmaps, leading end-to-end ML development, partnering with engineering and product teams, shaping technical vision for future AI commerce scenarios, driving improvements in customer satisfaction and business outcomes, and mentoring scientists and engineers. Required qualifications include advanced degrees in relevant fields with 5+ to 8+ years of experience, extensive experience building large-scale ML systems, deep expertise in modern ML techniques, technical leadership experience, and domain experience in advertising, e-commerce, and AI-powered assistants. The position is full-time, on-site in Redmond, WA or Mountain View, CA, with a salary range of $165,600 to $296,400 USD annually, higher in certain metro areas.
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Mountain View, United States; Redmond, United States
Full-time
Serve as the technical lead for AI-powered relevance, shopping, recommendation, and agentic commerce initiatives across Copilot, Shopping, and Ads experiences
Drive innovation in machine learning technologies including LLMs, SLMs, multimodal AI, retrieval, ranking, personalization, and recommendation systems
Define and execute the science roadmap for user intent understanding, product understanding, content relevance, and advertiser matching
Lead end-to-end ML development including model architecture, training data strategy, evaluation, experimentation, calibration, and production deployment
Partner with engineering and product teams to deliver scalable, reliable, and cost-efficient AI systems
Shape the technical vision for future agent experiences, conversational shopping, and AI-assisted commerce scenarios
Drive measurable improvements in customer satisfaction, engagement, relevance quality, and business outcomes
Mentor scientists and engineers while raising the technical bar across machine learning, experimentation, and scientific rigor
Requirements
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience
OR equivalent experience
Preferred: Master's Degree AND 12+ years related experience
Preferred: Doctorate AND 8+ years related experience
Extensive experience building and shipping large-scale machine learning systems in search, recommendation, ranking, advertising, commerce, conversational AI, or personalization
Deep expertise in modern machine learning including deep learning, transformers, representation learning, retrieval systems, recommendation systems, and foundation models
Experience as a technical lead for large-scale cross-organizational initiatives
Proven ability to translate research innovations into production systems with measurable business impact
Experience with LLMs, SLMs, multimodal AI, and agentic systems
Experience in advertising, e-commerce, shopping, recommendation, or marketplace ecosystems
Experience developing AI-powered assistants, commerce experiences, or personalization platforms
Experience optimizing distributed training and inference systems on large GPU clusters
Experience mentoring principal-level engineers, scientists, and technical leaders
Certain roles may be eligible for benefits and other compensationLink to additional benefits and pay information: https://careers.microsoft.com/us/en/us-corporate-pay
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