Building The Next Generation of Night Vision Devices

Applied AI Research Scientist - Computational Imaging

$300K - $600K / 3.00%
San Francisco, CA, US / Remote (US)
Job Type
1+ years
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Lucas Young
Lucas Young

About the role

DeepNight is a seed-stage startup that leverages the latest advancements in AI to push the boundaries in computational imaging at the edge.

We are seeking a talented Applied AI Research Scientist specializing in computational imaging to join our team. You will be responsible for conducting innovative research and developing advanced algorithms at the intersection of artificial intelligence and imaging technology.


  • Conduct research to explore novel approaches in computational imaging, leveraging artificial intelligence and machine learning techniques.
  • Implement and optimize algorithms for real-time or near-real-time applications, considering computational efficiency and hardware constraints.
  • Evaluate and validate algorithms using experimental data and real-world scenarios, ensuring robust performance and reliability.
  • Stay up-to-date with the latest advancements in AI, machine learning, and imaging technology, and integrate relevant techniques into research projects.
  • Publish research findings in peer-reviewed conferences and journals, and contribute to patent applications when applicable.

Preferred Requirements:

  • Ph.D. or equivalent experience in Computer Science, Electrical Engineering, or related field, with a focus on artificial intelligence, machine learning, computer vision, or computational imaging.
  • Strong research background with a track record of publications in top-tier conferences or journals in relevant fields.
  • PyTorch experience.
  • Solid understanding of imaging principles, including optics, sensors, and image formation processes.

About DeepNight

DeepNight is building night vision with AI software. We are pushing the state of the art of computational imaging to build a new generation of night vision goggles that see in the dark using AI. We conduct novel research in computational photography, novel efficient neural architectures, and model compression techniques to build extremely efficient AI on the edge.

Team Size:3
Location:San Francisco
Thomas Li
Thomas Li
Lucas Young
Lucas Young