This role offers a meaningful leadership opportunity: managing a diverse team that includes researchers, MLOps engineers, and data management experts, while shaping the teams technical direction and influencing product directions in close partnership with product and system engineering teams, all within a culture that values inclusion, collaboration, continuous learning, and individual growth.
The teams primary focus is developing state-of-the-art computer vision solutions that can run efficiently under real-world edge-device constraints, including model size, latency, power, and deployment efficiency. In parallel, the team explores similar optimization opportunities for SLMs, enabling advanced AI models to run more efficiently across Windows products.
In this role, you will help turn applied research into production-quality AI experiences, collaborate closely with product, system engineering, software, and silicon teams, and create impact for millions of customers.
Responsibilities
Lead, grow, and develop a diverse data science team that includes researchers, MLOps engineers, and data management experts, while fostering a culture of technical excellence, collaboration, ownership, and continuous learning.
Define and drive the teams technical roadmap in close partnership with product and system engineering teams.
Guide the development of production-oriented AI solutions from research exploration through production deployment, with a strong focus on quality, scalability, reliability, and measurable customer impact.
Drive model efficiency and deployment readiness for constrained environments, ensuring AI solutions meet real-world requirements for performance, latency, footprint, and resource usage.
Mentor team members, create clarity, set priorities, and help the team deliver high-impact results in a dynamic and evolving environment.
Qualifications
M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related technical field.
Experience in computer vision, efficient small language models, or related AI model development areas
Experience as a people manager or as a technical leader driving work across a team.
Preferred Qualifications
Hands-on experience with computer vision systems deployed in production or resource-constrained environments.
Hands-on experience with model development, evaluation, optimization, compression and efficient inference for edge devices.
Experience bringing AI solutions from research or prototyping into production environments.
Experience working with MLOps, data pipelines, model lifecycle management, or production AI infrastructure.
Demonstrated ability to motivate people, create clarity, and drive execution.
High motivation, ownership mindset, strong collaboration skills, and the ability to influence across disciplines.
