AR Wearables: Photon-Efficient CV & ML Engineer

Snap Inc.; Greater London; Hybrid; GBP 110,000 - 150,000; Full time

Benefits offered by this job

Paid parental leave

Medical coverage

Mental health support

Long-term incentives

Job summary

Snap Inc. is seeking a Computer Vision & Machine Learning Engineer for photon-efficient, event-driven imaging, based in our London office.

You’ll design, train, and deploy CV/ML models tailored to low-light, high-temporal-resolution data, collaborating with global hardware and software teams to push wearable AR capabilities. You’ll tackle tracking, depth estimation, and SLAM, advancing feature algorithms for next-generation AR glasses.

Qualifications

• Experience with photon-efficient or event-driven imaging systems (e.g. VIO, SLAM, Hand tracking)
• Strong background in computer vision, machine learning, and statistical signal processing
• Solid math background with deep understanding of 3D geometry, probability, statistics, and linear algebra
• Ability to transform ideas into clean, fast and reliable code
• Attention to detail, strong communication skills
• 5+ years of post-Bachelor’s relevant experience; or Master’s degree in a technical field + 4+ years of relevant post-grad experience; or PhD in a relevant technical field + 2 years of relevant experience
• Track record of successful projects showing computer vision skills in photon efficient or event‑based imaging
• 5+ years of programming experience in C++ and Python (e.g. PyTorch, TensorFlow)

Responsibilities

• 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
• Develop novel photon-efficient imaging features and algorithms for the next generation of AR Glasses
• 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
• Work with our computer vision team to deliver next‑generation detection (such as face, hand, body etc.) technology for augmented reality systems

Skills

Photon-efficient imaging

Event-driven imaging

Computer vision

Machine learning

3D geometry

Programming in C++

Programming in Python

Education

Master’s degree in a technical field

PhD in a technical field

Bachelor’s degree + 4+ years experience

Tools

PyTorch

TensorFlow

Python

C++

Job description

Snap Inc. is seeking a Computer Vision & Machine Learning Engineer for photon-efficient, event-driven imaging, based in our London office.

You’ll design, train, and deploy CV/ML models tailored to low-light, high-temporal-resolution data, collaborating with global hardware and software teams to push wearable AR capabilities. You’ll tackle tracking, depth estimation, and SLAM, advancing feature algorithms for next-generation AR glasses.