Lead research, incubation, and productization of computer vision, multimodal AI, machine learning, and media intelligence technologies. Establish technical direction for model architecture, training methodologies, evaluation frameworks, and deployment strategies. Lead, coach, and grow a high-performing team of Applied Scientists and Engineers. Foster a culture of innovation, scientific rigor, experimentation, customer obsession, and operational excellence. Attract, recruit, develop, and retain world-class talent across machine learning, computer vision, and AI. Create growth opportunities and technical mentorship pathways for team members. Drive alignment across distributed organizations working on AI-powered media experiences. Represent Media Intelligence in leadership reviews, architecture forums, investment discussions, and strategic planning processes. Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research). 1+ year(s) of people management experience. These requirements include but are not limited to the following specialized security screenings: Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 5+ years of people management experience. 5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers). 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker. 5+ years experience conducting research as part of a research program (in academic or industry settings). 3+ years experience developing and deploying live production systems, as part of a product team. 3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping. Multiple years of experience managing scientists, machine learning engineers, or advanced technical teams. Demonstrated experience delivering production AI, machine learning, or computer vision systems at scale. Computer Vision Machine Learning Deep Learning Multimodal AI Video Processing Media Systems Large-scale Inference Platforms Proven track record of translating research innovation into customer-facing products. Experience leading cross-functional initiatives involving engineering, product management, and research organizations. Communication, leadership, and stakeholder management skills. Experience building multimodal foundation-model powered systems. Experience with real-time media, video conferencing, streaming, telecommunications, or collaboration technologies. Background in AI-powered perception systems, visual understanding, speech/vision integration, or agentic AI systems. Knowledge of model optimization, edge inference, NPU/GPU acceleration, and large-scale cloud inferencing. Experience developing evaluation frameworks, benchmarking systems, and quality measurement methodologies for AI models. Experience partnering with research organizations and leading incubation-to-product transitions. Demonstrated ability to influence organization-wide technical strategy and investment decisions. Establish metrics, experimentation frameworks, and evaluation methodologies for scientific investments. Ensure scalable engineering and model development processes that enable rapid innovation while maintaining service quality and reliability. Builds trust across disciplines and organizations. Develops future leaders and fosters an inclusive, high-performing team culture.