Computer Vision & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging

Snap Inc.

Confirmed live yesterday High trust

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Work type
On-site
Location
London, United Kingdom
Posted
2 days ago
Freshness
Confirmed live yesterday
Nearby
41 roles within 25 mi

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Similar $214k
$138k most similar roles pay here $277k

This listing doesn't post a salary. Most similar roles pay $186,975–$241,750.

Based on 240 similar postings.

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About Snap Inc.

Snap Inc. is a technology and camera company, best known for Snapchat, offering visual communication, augmented reality, and advertising products.

Snap Inc. currently has 75 open roles on FindRole.

Listed pay typically runs $209,000–$313,000 across 64 roles with salary data.

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TL;DR · Computer Vision & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging

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As a Computer Vision & Machine Learning Engineer, Photon-Efficient Event-Driven Imaging, you will join the Spectacles Computer Vision Team to solve complex challenges in ultra-low-light and high-temporal-resolution imaging. You will design, train, and deploy machine learning models and computer vision algorithms specifically for photon-efficient, event-driven systems used in next-generation wearable devices. Your daily work involves developing state-of-the-art tracking, depth estimation, SLAM, and detection technologies like face and body tracking for augmented reality. To succeed, you must possess a strong foundation in statistical signal processing, 3D geometry, probability, and linear algebra. You will utilize C++, Python, PyTorch, and TensorFlow to build robust code. This role focuses on the technical challenge of creating high-performance imaging features that improve speed and noise robustness for wearable hardware within the augmented reality domain.

Skills

Computer Vision Machine Learning C++ Python PyTorch TensorFlow SLAM 3D Geometry Signal Processing Augmented Reality Event-Driven Imaging Linear Algebra Probability Statistics

What you'll do

  • Design, train, and deploy machine learning models for photon-efficient, event-driven imaging systems.
  • Develop computer vision algorithms tailored for high-temporal-resolution data.
  • Contribute to tracking, depth estimation, and SLAM systems using event-driven data.
  • Create novel photon-efficient imaging features for next-generation AR glasses.
  • Research machine learning and probabilistic techniques to improve speed and noise robustness.
  • Develop detection technologies for faces, hands, and bodies in augmented reality systems.
  • Translate complex ideas into clean, fast, and reliable code using C++ and Python.

What we're looking for

  • 3+ years of industry experience in computer vision for photon-efficient or event-driven imaging.
  • Experience with photon-efficient or event-driven imaging systems.
  • Track record of successful projects demonstrating computer vision skills.
  • 3+ years of programming experience in C++ and Python (e.g., PyTorch, TensorFlow).
  • Solid foundation in computer vision, machine learning, and statistical signal processing.
  • Strong math background including 3D geometry, probability, statistics, and linear algebra.
  • Ability to translate ideas into clean, fast, and reliable code.

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