Startups · AI

Applications Engineer, San Francisco

Overview · San Francisco · Remote

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About Overview

Backed by Y Combinator and GV.

About the role

This is a hands on machine vision role for someone who wants to get deep, fast. You will split your time between the lab and live customer applications: evaluating a lens, optimizing a camera setup, building a proof of concept, troubleshooting an inspection that has to hold on a production line. The work moves from bench to factory floor in weeks, not quarters, and what you learn in the lab shows up directly in what we deploy.

What they're looking for

  • Required
  • 1 to 3+ years in machine vision, computer vision, applications engineering, robotics, automation, manufacturing, or a related field
  • Strong hands on grasp of machine vision fundamentals: cameras, lenses, optics, lighting, and image acquisition
  • Familiarity with lens types and when to use them, including telecentric lenses
  • Working understanding of AI based vision and how it differs from traditional rules based vision
  • Familiarity with image labeling, model training, classification, object detection, and segmentation
More about this role

Applications Engineer

San Francisco, CA · Applications · Full time, in office

Travel: Up to 50%, typically lower.

ABOUT OVERVIEW.AI

Overview.ai is bringing the cutting edge of AI computer vision to manufacturing, solving inspection problems that were previously not solvable with traditional machine vision. We're a full-stack company: we deploy GPU-powered cameras on production lines, run inference on the edge, and operate a platform that supports large fleets of devices deployed across the world.

We're growing extremely fast. Our customers love the product because it works: high accuracy, fast deployment, and an operator-friendly experience that makes real factory rollouts possible, not just pilots.

This is a hands on machine vision role for someone who wants to get deep, fast. You will split your time between the lab and live customer applications: evaluating a lens, optimizing a camera setup, building a proof of concept, troubleshooting an inspection that has to hold on a production line. The work moves from bench to factory floor in weeks, not quarters, and what you learn in the lab shows up directly in what we deploy.

Become a genuine machine vision expert: optics, lighting,...

Read the full posting on Overview's site ↗

Overview US

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