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Deep Learning Infrastructure Engineer

Overview

San Francisco, CA, US
  • 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. Delivering on reliable and accurate models is a key component of this. We are looking for someone who knows the ins and outs of DL infra to help us scale up.

Responsibilities

  • Working on automating CV/DL pipeline, including identifying and solving for bottlenecks
  • Choosing and implementing the best tools to strengthen our pipeline
  • Collaborate with our DL engineers to get high performing models into customers hands
  • Build, manage, scale our training pipeline
  • Developing tools that monitor models to ensure long term stability and accuracy
  • Tooling around active learning to improve models over time and avoid model drift

Helpful Experience

  • Having deployed models to several platforms including edge devices and cloud
  • Experience with Jetson Jetpack and/or Triton Inference Server
  • Managing TensorRT or ONNX deployments
  • Having managed an end to end deep learning project from data collection to deployment
  • Experience with Docker
  • Experience with Python/C++

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.

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