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

As a Computer Vision & ML Engineer on the Spectacles team in London, you will help advance photon-efficient, event-driven imaging for next-generation AR wearables. You’ll collaborate with Snap’s hardware and software groups to design and deploy ML models and CV algorithms, contributing to tracking, depth estimation, and SLAM in high-temporal-resolution data. This role blends cutting-edge imaging research with practical implementations to enable camera-first experiences. You join a world-class team shaping wearable computing and AR glasses.

• paid parental leave
• comprehensive medical coverage
• emotional and mental health support programs
• compensation packages linked to Snap’s long-term success

• Design, train, and deploy machine learning models and CV algorithms for photon-efficient, event-driven imaging systems
• Advance tracking, depth estimation, and SLAM using high-temporal-resolution event-driven data
• Develop novel photon-efficient imaging features for AR glasses
• Explore ML and probabilistic techniques to boost speed, noise robustness, and accuracy of CV systems
• Contribute to detection capabilities (face, hand, body) for AR systems

• 5+ years of post-Bachelor’s relevant experience; or Master’s degree + 4+ years; or PhD + 2 years
• Experience with computer vision for photon-efficient or event-driven imaging systems (e.g. VIO, SLAM, Hand tracking)
• 5+ years programming in C++ and Python (e.g. PyTorch, TensorFlow)
• Strong foundation in CV, ML, and statistical signal processing
• Solid math background in 3D geometry, probability, statistics, and linear algebra
• Ability to translate ideas into clean, fast, reliable code
• Attention to detail and strong communication; outstanding problem-solving skills

• Attention to detail
• Clear communication
• Problem-solving
• Photon-efficient, event-driven imaging
• Computer vision and machine learning
• VIO/SLAM/Hand tracking