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

Join Snap Inc. as a Computer Vision & Machine Learning Engineer on the Spectacles Computer Vision Team. You will work on solving challenges in ultra-low-light and high-temporal-resolution imaging, developing novel algorithms for photon-efficient, event-driven imaging systems for the next generation of wearable devices.

This role requires a solid foundation in computer vision, machine learning, and statistical signal processing, as well as experience with photon-efficient or event-driven imaging systems. You will collaborate closely with other Snap hardware and software teams around the world and work from the London office.

• Design, train, and deploy machine learning models and computer vision algorithms tailored for photon-efficient, event-driven imaging systems.
• Contribute to state-of-the-art tracking, depth estimation, and SLAM and ML systems leveraging high-temporal-resolution event-driven data.
• Research new machine learning and probabilistic techniques to improve speed, noise robustness, and accuracy of computer vision algorithms in photon-efficient, event-driven imaging systems.

• Solid math background with deep understanding of 3D geometry, probability, statistics, and linear algebra
• Solid foundation in photon-efficient, event-driven imaging systems
• Ability to transform ideas into clean, fast and reliable code
• Attention to detail, strong desire for quality and good communication skills
• Solid foundation in computer vision, machine learning, and statistical signal processing
• Outstanding problem solving skills
• Experience with photon-efficient or event-driven imaging systems
• BSc/MSc with 3+ years of relevant experience from industry in computer vision for photon-efficient or event driven imaging
• 3+ years of programming experience in C++ and Python (e.g. PyTorch, TensorFlow)
• Track record of successful projects showing computer vision skills