Director of Computer Vision

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Company Overview At Motorola Solutions, we believe that everything starts with our people. We're a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that's critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future. Department Overview Motorola Solutions' innovations, products, and services play essential roles in people's lives. Our end-to-end suite of software solutions helps customers manage emergency communications, process video and evidence, and leverage cutting-edge AI-driven analytics for security and operational insights. We are industry leaders in video security and analytics, with solutions deployed in more than 120 countries across diverse environments such as school campuses, transportation systems, healthcare centers, public venues, critical infrastructure, prisons, factories, casinos, airports, financial institutions, government facilities, and retailers. Our AI-powered security solutions integrate advanced video analytics, machine learning, and embedded intelligence to enable proactive threat detection, enhanced situational awareness, and automated decision-making. Job Description The Director of Computer Vision will drive the technical vision, research and engineering execution for the platform, with focus on the following core areas: Foundational Research Strategy: Define the long-term research agenda for fundamental computer vision capabilities and drive the culture of scientific excellence. Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to a unified research and engineering organization, defining the technical architecture, strategy, and engineering roadmap for the Computer Vision Platform. Drive execution, ensuring the seamless translation of product requirements into robust technical specifications and successful delivery of next-generation visual intelligence solutions that are highly scalable and align with overall product and business strategy. Organizational Leadership and Talent Strategy: Manage and scale a unified computer vision research and engineering organization distributed across multiple geographies, overseeing multiple teams, and defining the strategy for recruiting, mentoring, and attracting world-class talent. End-to-End MLOps and Deployment: Own the entire engineering lifecycle for central, reusable computer vision models and foundational AI infrastructure. This includes establishing best-in-class MLOps practices for scalable training, efficient deployment, continuous monitoring, and performance optimization across edge and cloud environments. Performance Measurement and Continuous Improvement: Define, implement, and track key technical performance metrics (e.g., latency, throughput, model efficiency, system reliability) to measure engineering success, identify bottlenecks, and drive continuous improvement in execution and delivery. Technical Innovation and Risk Management: Evaluate and integrate cutting-edge computer vision research and technologies. Proactively identify and mitigate significant technical risks, and lead critical engineering decisions, including build-versus-buy analysis. Qualifications & Experience 10+ years of technical leadership experience leading computer vision teams and organizations , with a focus on building and deploying enterprise-scale platforms and solutions in production. Technical Acumen & Deep Expertise: Deep, demonstrable expertise in computer vision, machine learning algorithms, and the end-to-end MLOps lifecycle, including 5+ years of hands-on experience building and optimizing computer vision models or as a computer vision researcher. Proven ability to engage in complex technical discussions, define the architectural vision for central, reusable AI infrastructure and models, and drive technical strategy while managing critical trade-offs. Executive Technical Strategy & Metrics: Proven experience defining long-term technical vision, engineering strategy, and roadmaps for a large-scale platform. Expertise in defining and implementing technical metrics (e.g., latency, throughput, system reliability, model efficiency) to measure engineering excellence and drive continuous improvement across an organization. Organizational & People Leadership: Demonstrated ability to manage and scale a unified, distributed engineering and research organization of 50 to 100 people, mentor senior technical talent, and lead multiple teams across different geographies. Strong Analytical and Research Skills: Hands-on experience driving innovation through foundational research, working with AI performance metrics (e.g., Precision/Recall), real-time video processing, and inference optimization. Customer-Driven Tech