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We are looking for an Applied Scientist to join our Video Search team, where you will help shape the future of how users discover and interact with video content at scale. In this role, you will bridge the gap between cutting-edge research and real-world product impact — translating advances in computer vision, multimodal understanding, and information retrieval into robust, production-grade systems. You will work closely with product, engineering, and research teams to design and evaluate models that power video search, ranking, and relevance. This is a role for someone who thrives at the intersection of research and engineering, and who is energized by the challenge of making complex AI systems work reliably for hundreds of millions of users.
Job Responsibility:
Design, develop, and evaluate machine learning models for video search, including video-text retrieval, multimodal ranking, query understanding, and relevance scoring
Collaborate with product and engineering teams to translate research findings into measurable improvements in search quality, latency, and user engagement
Partner with researchers in the broader community and Microsoft internally to identify and apply state-of-the-art methods in computer vision, NLP, and multimodal learning
Conduct rigorous experiments — define metrics, run A/B tests, analyze results, and communicate findings clearly to both technical and non-technical stakeholders
Stay current with advances in video understanding, dense retrieval, vision-language models, and related fields
assess their applicability to product problems
Document research processes, experimental results, and model decisions to support reproducibility and team knowledge sharing
Adhere to Microsoft's ethics and privacy policies throughout data collection, model development, and deployment processes
Contribute to a positive, inclusive team environment and, when asked, help identify prospective talent through your external research network
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
OR equivalent experience
1+ year of experience contributing to publications (peer-reviewed papers, patents, or equivalent)
Hands-on experience with video or multimodal ML systems (e.g., video-text retrieval, video captioning, temporal grounding, or visual search)
Familiarity with large-scale training frameworks (PyTorch, tensorflow) and experience working with web-scale data pipelines
Experience with search or ranking systems, including offline evaluation (NDCG, MRR) and online experimentation (A/B testing)