ZipCam | Multiple Positions | Full-Time | Remote (or Palo Alto) | www.zip.cam
ZipCam makes a smart, connected, automotive dashcam for driving safety. In the U.S., more than 37,000 lives per year are lost in automobile accidents. Worldwide, an unbelievable 1.25 million people die from car crashes annually. We don't need full L5 autonomous cars to save these lives: we can add computer vision and machine learning to existing vehicles, to save lives today.
ZipCam is seed-stage and well funded by angels. You should be a hands-on engineer, but management experience is a plus. Multiple positions available, all full-time, Onsite (Palo Alto) or Remote are OK:
* Midlevel or Senior Machine Learning Engineer. We do neural network analysis of driving video clips: lane-keeping, accident "near miss" detection, sign reading, stop light classification, stop line detection, other driving tasks. Also with a driver-facing camera: classification of various kinds of distraction (cell phone use, etc). You should have experience running accelerated ML models on video data. Experience with IoT is a plus. Low-power (embedded) inference experience is a plus.
* Experienced Android Engineer. We're looking for experience with video streaming, embedded devices, IoT, and intermittent data connections. Experience with the Google NNAPI is a plus. An eye for UI design is always welcome.
Drop us a line to learn more about the product roadmap, it's exciting. This is a historic moment for real-world ML applications. Please send your resume + linkedin &amp; github URLs to jobs - at - zip - dot - cam. Please include relevant publications or mention relevant projects you have done. Looking forward to speaking with you.
P.S. If you'll be at NeurIPS in Vancouver next week, let's meet up during the conference.