Director of Computer Vision

About the Role The Director of Computer Vision will drive the technical vision, research and engineering execution for Motorola Solutions' Computer Vision Platform, leading foundational research, architecture and delivery of scalable visual intelligence solutions across edge and cloud. What You'll Do

• Define the long-term foundational research strategy for computer vision capabilities and foster a culture of scientific excellence.
• Provide executive technical leadership to a unified research and engineering organization, defining the architecture, strategy and roadmap for the Computer Vision Platform.
• Translate product requirements into robust technical specifications and ensure successful delivery of next-generation vision solutions that are scalable and aligned with product and business strategy.
• Manage and scale a unified computer vision research and engineering organization distributed across geographies, overseeing multiple teams and defining strategy for recruiting, mentoring and attracting world-class talent.
• Own end-to-end MLOps and deployment for central, reusable computer vision models and AI infrastructure, including scalable training, deployment, monitoring and optimization across edge and cloud.
• Define and track key technical performance metrics (latency, throughput, model efficiency, system reliability) to measure engineering success and drive continuous improvement.
• Evaluate and integrate cutting-edge computer vision research and technologies; identify and mitigate significant technical risks and make critical build-versus-buy decisions. What We're Looking For
• 10+ years of technical leadership experience leading computer vision teams and organizations, with a focus on enterprise-scale platforms deployed in production.
• Deep expertise in computer vision, machine learning algorithms, and the end-to-end MLOps lifecycle; 5+ years hands-on experience building and optimizing computer vision models or as a computer vision researcher.
• Proven ability to define the architectural vision for central, reusable AI infrastructure and models, and to drive technical strategy while managing key trade-offs.
• Experience defining long-term technical vision, engineering strategy and roadmaps for large-scale platforms; expertise in technical metrics (latency, throughput, reliability, model efficiency).
• Demonstrated ability to manage and scale a distributed engineering and research organization (50–100 people), mentor senior technical talent, and lead multiple teams across geographies.
• Strong analytical and research skills with experience in AI performance metrics (e.g., Precision/Recall), real-time video processing, and inference optimization.
• Track record of translating ambiguous customer needs into concrete product concepts and technical roadmaps.