Applied Science Manager III, RBKS AI

The 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 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.

The team is focused on productizing research in computer vision and GenAI into products that benefit millions of customers worldwide such as real-time object detection video understanding and multimodal LLMs. We are at the forefront of developing AI solutions that seamlessly blend into our products while respecting privacy delivering unprecedented levels of intelligent security experience.

Key job responsibilities
- Lead 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
- Drive 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
- Partner with product and engineering leadership to translate business objectives into technical roadmaps and ensure delivery of high-quality science artifacts that ship to products
- Build and maintain strategic partnerships with science engineering product and program management teams across the organization
- Recruit mentor and develop top-tier applied science talent; provide technical and career guidance to team members while fostering a culture of innovation and excellence
- Set technical direction and establish best practices for AI products/features across multiple projects and initiatives

- 6 years of scientists or machine learning engineers management experience
- Experience managing multiple projects and priorities across teams in a fast-paced deadline-driven environment
- Technical depth in AI Computer Vision modern ML frameworks and infrastructure to guide team technical decisions and code reviews

- Experience with deep learning libraries such as PyTorch TensorFlow MxNet Research publications in computer vision deep learning or machine learning at peer-reviewed workshops conferences or journals
- Experience communicating across technical and non-technical audiences including executive level stakeholders or clients
- Experience leading development of real-time computer vision systems and optimization techniques at scale
- Experience setting technical vision and multi-year roadmaps for applied science teams

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