- Job Type: Full-Time
- Function: IT
- Industry: Supply Chain and Logistics
- Post Date: 11/27/2023
- Website: overview.ai
- Company Address: 736 Clementina St, San Francisco, CA, 94103
- Salary Range: $50,000 - $150,000
About Overview
Overview provides deep learning vision systems and a quality workflow platform. We help manufacturers save time and money with automated inspection and streamlined quality control.Job Description
At Overview we are building an end-to-end computer vision platform to democratize manufacturing's access to state of the art deep learning. Deploying highly reliable cameras/compute is core to our mission. We are looking for an IoT engineer who can help with the fleet management associated with all of our deployed devices. This person will also help make our IoT devices as compatible with as many factory settings as possible.
Responsibilities
- Working directly on our device client code that sits on the Nvidia Jetson
- Manage network connections to the device and monitoring security
- Working with video drivers and encoding libraries to optimize getting images efficiently from camera to GPU
- Working on device I/O with factoring systems like PLC's
- Sending diagnostics
Helpful Experience
- Worked on embedded devices like Jetson or Raspberry Pi
- Experience with pub/sub communication protocols like MQTT
- Deploying into edge environments using Docker
- Linux/OS system commands and bash scripts
- Worked directly with GPU using Cuda / OpenCL
- Handled video compression and encoding challenges
Why you should join Overview
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.