This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
Microsoft Advertising is building the next generation of intelligent systems that power how users discover relevant ads and how advertisers connect with customers across search, native, display, video, and emerging AI experiences. We operate at global scale, serving billions of requests. We are seeking a Senior Applied Scientist to work across a broad portfolio of applied machine learning problems in Ads. This role spans retrieval, ranking, marketplace quality, fraud and abuse detection, content understanding, moderation, and emerging foundation-model-powered experiences. The work entails developing and applying LLMs, large retrieval models, multimodal systems, and agentic or deep-research-style workflows to high-impact advertising scenarios at scale. This is an opportunity to work on frontier machine learning problems with direct production impact, improving relevance, quality, safety, efficiency, and advertiser outcomes at massive scale.
Job Responsibility:
Design and improve large-scale learning systems for matching, relevance, prediction, classification, and decision-making in production environments
Partner closely with product, and platform teams to productionize models and measure impact through rigorous offline and online experimentation
Analyze large-scale data to identify modeling opportunities, understand failure modes, and drive continuous improvements in product quality and system performance
Contribute to technical innovation through prototyping, experimentation, publications, patents, and strong scientific rigor
Requirements:
Bachelor's Degree in Computer Science, Statistics, Electrical Engineering, Computer Engineering, or related field AND 6+ years of related experience in applied science, machine learning, recommender systems, information retrieval, or related areas
OR Master's Degree in a related field AND 4+ years of related experience
OR Doctorate in a related field AND 2+ years of related experience
OR equivalent experience
Strong foundation in machine learning and depth in one or more relevant areas such as retrieval, ranking, recommender systems, representation learning, fraud detection, content quality, moderation
Experience building, evaluating, and shipping machine learning models in production environments
Ability to design experiments, analyze results, and make data-driven decisions in complex systems
Strong problem-solving, communication, and cross-functional collaboration skills
Nice to have:
Experience in Ads, search, recommendation systems, trust and safety, marketplaces, or other large-scale online platforms
Familiarity with large-scale distributed training, online inference systems, and latency-sensitive production services
Track record of technical impact through shipped systems, research publications in top tier conferences