Senior Computer Vision Engineer

About Invisible AI

Invisible AI, founded in 2018 in the San Francisco Bay Area, offers a computer vision platform to reduce manufacturing costs associated with manual assembly errors. Our edge-based AI-enabled cameras track body posture and movement to help complete the story of what is happening on an assembly line to prevent any mistakes. We have raised just over $6.5M in our seed round. Our main offices are located in Austin, TX and Ann Arbor, MI.
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Austin, TX
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Job description:

In addition to pushing the boundaries of existing deep learning technologies, you will be solving complex algorithmic challenges that deep learning alone cannot. You will be working with a world-class team of engineers to deploy a new wave of AI products that work out-of-the-box across domains without weeks or months of data collection.


  • Writing a machine learning pipeline from scratch based on a paper released on Arxiv. This project included developing the dataset loader, augmentation functions, deep learning model, and loss functions — the whole nine yards. And that was just a Tuesday.
  • Developing a new probabilistic model to track critical work in manufacturing facilities while ignoring day-to-day variations
  • Constraining the problem space creatively in order to develop a practical solution that can be deployed across facilities with very little fine tuning
  • Working on novel labeling methods with the data infrastructure team to reduce labeling costs while improving model outputs
  • Implementing new loss functions or model architectures so cool they would make waves at CVPR, when you deign to eventually share them
  • Using the temporal and consistent nature of video to reduce false positives in a deep learning model while exploring what’s possible in unsupervised object detection
  • Designing new application architectures to solve new customer problems
  • Developing end-to-end machine learning pipelines based on product requirement documents
  • Building new testing environments based on recent Arxiv papers with a focus on delivery speed
  • Reviewing team code and enforcing engineering best practices during the review process
  • Occasionally mentoring junior engineers on computer science and computer vision topics

Minimum Qualifications:

  • Have a research and problem solving background given complex problems
  • Have built or worked on deep learning training pipelines
  • Have worked on robotics and computer vision algorithms (ex: frame transformations, camera calibration, optical flow, etc.)
  • Have the ability to quickly hit the ground running and build training pipelines
  • Be passionate about AI and is ready to take risks in a fast-paced startup environment


1. Competitive compensation and equity packages

2. Health, vision and dental insurance

3. Flexible vacation schedule

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