Applied Scientist II, RBKS AI
Content + Source + Freshness • 14 Dec 2025 • 95% confidence
Offer value
Focuses on cutting-edge computer vision technology with an emphasis on developing practical AI solutions for consumer products.
- Work on groundbreaking computer vision and AI technologies
- Significant role in developing practical applications for consumers
- Career within a leading organization focused on innovation
- Requires strong technical expertise in ML and computer vision
Pros
- Cutting-edge focus on multi-modal sensor fusion in AI.
- Distinct challenges in computer vision and edge computing.
- Opportunity to impact consumer technology significantly.
Cons
- Roles may involve challenges matching innovative desires with practical constraints.
- Potentially high-pressure environment meeting production-level demands.
- Possible limited personnel support depending on project scale.
Who it's for
Mid-Level • Hybrid/Office
Good fit
- AI professionals skilled in computer vision technologies
- Candidates excited about consumer technology developments
- Individuals looking to innovate in edge computing
Not recommended for
- New entrants to the field without relevant expertise
- Those seeking positions with minimal technical complexity
- Candidates unwilling to work in a collaborative environment
Motivation fit
Key skills
About the job
Description
The Ring and Blink AI team (RBKS AI) is solving unique computer vision challenges at the intersection of edge computing, multi-modal sensor fusion, and visual language models. We process hundreds of millions of video events monthly across tens of millions of devices. We're looking for an Applied Scientist to tackle problems without off-the-shelf solutions.
Key job responsibilities
- Drive applied research in on-device computer vision and multi-modal ML, including object detection, tracking, event classification, and visual language understanding
- Balance innovation with pragmatism by shipping models that meet strict production requirements - latency, memory, power, and accuracy
- Own the complete ML lifecycle, from problem formulation and dataset curation to model development, edge optimization, and production validation at scale
- Advance the field by publishing novel techniques, filing patents, and contributing to the research community while delivering production-ready models
