Manager, Machine Learning Engineering

Manager, Machine Learning Engineering – Video Ai & Studio AiWe build next-generation AI systems for video, spanning both large-scale video understanding and creative studio workflows. Our work combines computer vision, multimodal learning, and machine learning to enable capabilities such as scene understanding, metadata generation, visual effects, storyboarding, and color enhancement across media content.We focus on taking ML from research to production, integrating models into real-world systems used by engineering, product, and creative teams. Our goal is to build scalable, high-quality solutions that power both content intelligence and creative workflows.What You'll DoLead a team of machine learning engineers working on video AI across understanding and creative applicationsStay hands-on, contributing directly to modeling, prototyping, and production systemsDrive execution across the full ML lifecycle: problem definition, modeling, evaluation, and deploymentPartner with product, creative, and engineering teams to define priorities and deliver impactful ML-powered featuresBuild and scale production-grade ML systems for video understanding and creative workflowsBalance rapid iteration with building robust, scalable systemsProvide technical leadership and mentorship, raising the bar for ML and engineering practicesCollaborate with platform and infrastructure teams to ensure reliable and scalable solutionsQualifications & Experience8+ years of experience in machine learning / software engineering, with a focus on computer vision, video understanding, and gen AI2+ years of experience leading or mentoring engineers, with a strong preference for hands-on leadershipStrong experience with deep learning frameworks (e.g., PyTorch, TensorFlow)Proven track record of building and deploying end-to-end ML systems in productionStrong background in computer vision, video understanding, or multimodal systemsExperience with large-scale datasets and distributed systemsExperience with generative AI techniques (e.g., diffusion, image/video generation)Strong system design and architecture skillsAbility to operate in ambiguous, fast-moving environments while maintaining execution focusStrong collaboration and communication skills across technical, product, and creative teams