OverviewMicrosoft Monetization is building the next generation of AI-powered advertising and commerce experiences across Search, Shopping, Copilot, and emerging agentic surfaces. As conversational agents increasingly become the interface between users and businesses, we are reimagining how products, services, and ads are discovered, selected, personalized, and delivered.
We are seeking a
Principal Applied Scientist and Technical Lead to drive the science vision, technical strategy, and execution for relevance, intent understanding, personalization, recommendation, and agent-driven commerce experiences.
This individual will serve as the technical leader across multiple science areas, influencing architecture, research investments, model roadmaps, and execution strategies while remaining deeply hands-on in machine learning innovation.
The successful candidate will combine deep expertise in machine learning and AI with a proven record of technical leadership, driving end-to-end innovation from research and experimentation through large-scale production deployment.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities- 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.
QualificationsRequired Qualifications:- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
Preferred Qualifications:- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent 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.
- Demonstrated experience serving 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.
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Applied Sciences IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
