We're hiring engineers to work on classification, systems, and core engineering for automated classification of online video. We use Python, linux, and make extensive use of AWS (do you like to play with MASSIVE data sets?).
Our product technology is a bit different than anyone else's right now; it uses machine learning and computer vision to watch and classify internet video, frame by frame, at large scale.
To put this in context, let’s say that the average video is three minutes long and there are 50 million videos put online every month. That’s 150 million minutes of online video published monthly. If you hired people to watch and categorize every single one of them, you’d need 3,422 people working 24/7 to do what SET technology does. What’s more, we don’t just know that a given video contains sports, we know it’s soccer, hockey, or basketball. And we know whether it’s safe or not fit for a customer's brand."
Our API provides extremely low latency responses to clients asking questions about page- and video-level. Our Dashboard provides reports generated from large amounts of raw data.
Our product technology is a bit different than anyone else's right now; it uses machine learning and computer vision to watch and classify internet video, frame by frame, at large scale. To put this in context, let’s say that the average video is three minutes long and there are 50 million videos put online every month. That’s 150 million minutes of online video published monthly. If you hired people to watch and categorize every single one of them, you’d need 3,422 people working 24/7 to do what SET technology does. What’s more, we don’t just know that a given video contains sports, we know it’s soccer, hockey, or basketball. And we know whether it’s safe or not fit for a customer's brand."
Our API provides extremely low latency responses to clients asking questions about page- and video-level. Our Dashboard provides reports generated from large amounts of raw data.
lars at set dot tv