Manufacturing Applications Engineer at Overview (W19)
Computer Vision Platform for Manufacturing
San Francisco / Remote
1+ years
About 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.

About the role
Skills: CAD Design

We are looking for a mechanical/manufacturing engineer to execute commercial projects after the sale has been made. Projects have a variety of technical aspects ranging from equipment selection and sourcing, to custom part design, to software integration. We are looking well-organized, doers, who can drive projects forward and interface with an internal team and multiple customers.

No candidates will have complete experience in all areas, but candidates should have comfort with CAD, custom design, and project management.

This role will naturally link with product development because the application work will require frontline use of our core product and areas for improvement should be uncovered.


Overview's tech is far reaching. We deploy highly reliable camera hardware and GPU's into manufacturing and industrial settings. We have an IoT fleet management stack to update, secure, and manage our fleet of devices. We stream this data to our cloud or to a customers hybrid cloud where we have a user facing platform where customers can interact with their devices, deploy new deep learning models, and see advanced analytics.

We use Docker to deploy web infrastructure and deep learning models. We have an extensive deep learning stack using Tensorflow, PyTorch and packaged with Onnx. Our frontend is in React, which is updated in real time from our fleet using MQTT. And the list goes on...

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