Overview:

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.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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- 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.

Qualifications:

Required Qualifications:

• 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 (Py Torch, 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).

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This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.