Standard Cognition | Researchers and Engineers | San Francisco, CA | Full-time, onsite | 120k-180k
We're using machine vision to build zero-friction checkout for stores. Walk in, grab stuff, and leave. Our system figures out what you grab and charges you automatically. Checkout what our real-time inference engine looks like <a href="
If you love hard problems, machine vision, and building products that change the way we interact with the world we'd love to talk with you. We're a young team that's moving fast and looking for people that love to rapidly iterate on challenging ideas. We're a YC company that's VC backed, 7 strong, and looking to grow. Two of our cofounders are UCSB alumns, so we'd love to hear from you.
Research Candidates
We're looking for strong deep learning and machine learning researchers to help lead our research programs. We view deep learning as a science, not an art, and we're looking for strong scientists: people that can generate, test, and refine hypotheses rapidly, with minimal bias. Fail fast, fail often. That's the mantra of startups, and that's the mantra of science. Help us rapidly generate targeted hypotheses and approaches for building a system that can comprehend the massive amount of video footage we feed it. If you're expertise isn't in machine vision but you're a passionate tinkerer or researcher in ML or deep learning we're happy to get you up to speed on the state of the art in vision.
Engineering Candidates
We're looking for strong Python engineers to help develop and productionize soft real-time algorithms in our vision pipeline. We have lots of big problems to solve. Engineers looking to lead and take on hard projects are welcome. Take cutting-edge research that requires massive clusters to work and make it run in real time on a single machine. Take disparate research results and merge them together into more powerful models. Build a massively parallel system that can comprehend 100Gbps of raw footage streaming from hundreds of cameras.
Experience in some of these areas is a plus: high performance and scientific computing, cluster management, deep learning, image processing, performance optimization, algorithmic research. Experience with some of these tools is a plus: cython, numpy, TensorFlow or some other deep learning framework, opencv, nix. If you're smart, passionate, and can learn fast on the job, we're happy to train an engineer in any and all of these areas.
Ask HN: Who is hiring? (October 2017)