Director of Computer Vision

Motorola Solutions•Washington, DC

5d•$250,000 - $290,000•Remote

About The Position

Motorola Solutions is seeking a Director of Computer Vision to lead the technical vision, research, and engineering execution for their platform. This role focuses on foundational research strategy, defining the long-term research agenda for computer vision capabilities and fostering scientific excellence. The Director will provide executive technical leadership to a unified research and engineering organization, defining the technical architecture, strategy, and roadmap for the Computer Vision Platform. They will drive the seamless translation of product requirements into robust technical specifications and ensure the successful delivery of next-generation visual intelligence solutions that are highly scalable and align with overall product and business strategy. Additionally, the role involves managing and scaling a unified computer vision research and engineering organization across multiple geographies, overseeing multiple teams, and defining strategies for recruiting and mentoring world-class talent. A key responsibility is owning the end-to-end engineering lifecycle for central, reusable computer vision models and foundational AI infrastructure, 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 through defining and tracking key technical metrics are also crucial, as is evaluating and integrating cutting-edge computer vision research and technologies while proactively managing technical risks.

Requirements

Bachelors degree with 10+ years of technical leadership experience leading computer vision teams and organizations.
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.
Deep, demonstrable expertise in computer vision, machine learning algorithms, and the end-to-end MLOps lifecycle.
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.
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.
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.
Hands-on experience driving innovation through foundational research, working with AI performance metrics (e.g., Precision/Recall), real-time video processing, and inference optimization.
Track record of translating highly ambiguous product concepts and complex customer needs into clear, executable technical roadmaps and architectural specifications.
Experience in a start-up or fast-paced environment is highly valued, demonstrating high ownership, bias for action, comfort with ambiguity, and the ability to drive 0-to-1 product development with limited resources.

Nice To Haves

Domain Knowledge: Experience in public safety, security-focused software (e.g., video security, evidence management), mission-critical systems, or emergency communications is a plus.

Responsibilities

Define the long-term research agenda for fundamental computer vision capabilities and drive the culture of scientific excellence.
Provide executive technical leadership to a unified research and engineering organization.
Define 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.
Manage and scale a unified computer vision research and engineering organization distributed across multiple geographies.
Oversee multiple teams, and define the strategy for recruiting, mentoring, and attracting world-class talent.
Own the entire engineering lifecycle for central, reusable computer vision models and foundational AI infrastructure.
Establish best-in-class MLOps practices for scalable training, efficient deployment, continuous monitoring, and performance optimization across edge and cloud environments.
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.
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.