Applied Scientist III, RBKS AI

The RBKS AI team is responsible innovating AI features for Ring and Blink cameras, with a mission to make our neighborhood safer. We are working in the intersection of computer vision, generative AI (GenAI), and ambient intelligence. The team is seeking AI Applied Scientists to work on initiatives that combine advanced computer vision and multimodal GenAI capabilities.

This role offers a unique opportunity to shape next-generation home security technology while 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

* Design and develop advanced computer vision and GenAI models and algorithms for comprehensive video understanding, including but not limited to object detection, recognition and spatial understanding

* Develop privacy-preserving CV and GenAI models and systems, focusing on efficient fine-tuning and on-device and in-cloud inference

* Map product requirements into science solutions and deliver high-quality science artifacts that ship to products

* Collaborate with scientists, engineers, product/program managers and other cross-functional teams

* Provide technical leadership on AI products/features, and develop and mentor junior scientists on the team.
- PhD, or Master's degree and 8+ years of applied research experience
- Proven expertise in developing and optimizing computer vision models, multimodal LLMs
- Proficiency in Python or other script programming languages
- 5+ years hands-on experience with computer vision and GenAI frameworks (e.g., PyTorch, Jax, etc.)
- Experience dealing well with ambiguity, prioritizing needs, and delivering measurable results in an agile environment

- Experience with hardware-software co-design for CV and GenAI applications
- Background in visual transformers, diffusion models, and multimodal generation
- Expertise in real-time computer vision systems and optimization techniques
- Expertise in efficient training and deployment of vision models and multimodal large language models
- Published research in top-tier conferences (CVPR, ICCV, NeurIPS, ICML) focusing on computer vision and/or GenAI

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