PpThe RBKS AI team is responsible for innovating AI features for Ring and Blink cameras, with a mission to make our neighborhoods safer. We are working at the intersection of computer vision, generative AI (GenAI), and ambient intelligence. The team is seeking an Applied Science Manager to lead initiatives that combine advanced computer vision and multimodal GenAI capabilities. This role offers a unique opportunity to lead a world‑class team while shaping next‑generation home security technology and advancing the field of AI algorithms and systems. /p h3Key job responsibilities /h3 ul liLead and guide a team of applied scientists in designing and developing advanced computer vision and GenAI models and algorithms for comprehensive video understanding, including but not limited to object detection, recognition, and spatial understanding. /li liDrive technical strategy and roadmap for privacy‑preserving CV and GenAI models and systems, ensuring the team delivers efficient fine‑tuning and on‑device and in‑cloud inference solutions. /li liPartner with product and engineering leadership to translate business objectives into technical roadmaps, and ensure delivery of high‑quality science artifacts that ship to products. /li liBuild and maintain strategic partnerships with science, engineering, product, and program management teams across the organization. /li liRecruit, mentor, and develop top‑tier applied science talent; provide technical and career guidance to team members while fostering a culture of innovation and excellence. /li liSet technical direction and establish best practices for AI products/features across multiple projects and initiatives. /li /ul h3Basic Qualifications /h3 ul li6+ years of scientists or machine learning engineers management experience. /li liExperience managing multiple projects and priorities across teams in a fast‑paced, deadline‑driven environment. /li liTechnical depth in AI, computer vision, modern ML frameworks, and infrastructure to guide team technical decisions and code reviews. /li /ul h3Preferred Qualifications /h3 ul liExperience with deep learning libraries such as PyTorch, TensorFlow, or MxNet. /li liResearch publications in computer vision, deep learning, or machine learning at peer‑reviewed workshops, conferences, or journals. /li liExperience communicating across technical and non‑technical audiences, including executive level stakeholders or clients. /li liExperience leading development of real‑time computer vision systems and optimization techniques at scale. /li liExperience setting technical vision and multi‑year roadmaps for applied science teams. /li /ul pAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. /p /p #J-18808-Ljbffr