Factories are highly complex systems. In some cases the manufacturing can happen too fast for humans to interact with. In other cases, workers are exposed to dangerous, physically demanding, and repetitive tasks all day long. In either case, at Overview we help the workers by providing factories with state-of-the-art AI solutions, to act as an extra set of eyes. This reduces repetitive tasks, and helps factories increase their efficiency. We don't just identify production issues in real-time. Our customers change their production processes around Overview's platform.
We are a YCombinator backed startup based in San Francisco, California. We are a small hybrid-remote team of awesome engineers working on an end-to-end platform: camera/sensor installations in factories to AI R&D. We provide clients a simple, reliable and powerful platform allowing to monitor their factories, making everyone's job easier, thanks to advanced deep learning and computer vision.
We are looking for someone to help innovate even more during our time of rapid growth, and who believes in our mission. A Deep Learning Data Scientist (Research) who wants to join our team of passionate people, striving to get the best out of our customer's data. Improving the accuracy and speed of our models will allow us to better help our customers
Responsibilities
Helpful Experience
Overview is a company that takes the cutting edge in computer vision and deep learning and applies it to previously unsolvable manufacturing inspection problems. We are truly a full stack company. We install physical cameras into the facility, run inference on the edge and manage massive deployments. Overview also streams gigabytes of video/image data to the cloud for our web platform to give customers advanced insights and analytics.
We are looking for engineers who like to solve tough challenges across the stack. This might include wrangling 500mb images or deploying optimized models in one click that can handle 10 parts a second. We are looking for people who are dynamic, who are excited to work on a different challenge every week, whether it's the final inspection on a medical device or making sure a razor blade has a perfect edge.