Photon-Efficient CV & ML Engineer for AR Wearables

SNAP, Inc.; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Parental leave

Fertility benefits

Backup childcare

Well-being programs

Dental coverage

Vision coverage

Life insurance

Gym perks

Retirement benefits

Discounts

Job summary

SNAP, Inc. in London is seeking a Computer Vision & Machine Learning Engineer to tackle challenges in ultra-low-light, high-temporal-resolution imaging for wearable AR devices.

You will design algorithms and models tailored for photon-efficient, event-driven imaging systems and collaborate across global teams. You will work on tracking, depth estimation, and SLAM, developing features for the next generation of AR glasses, while delivering fast, robust code and contributing to a strong CV/ML

Qualifications

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

Responsibilities

• Design, train, and deploy ML models and CV algorithms for photon-efficient, event-driven imaging.
• Contribute to state-of-the-art tracking, depth estimation, and SLAM for AR systems.
• Develop imaging features for next-generation AR Glasses.
• Research probabilistic techniques to improve speed, noise robustness, and accuracy.
• Collaborate with global Snap hardware and software teams on wearable imaging.
• Translate ideas into clean, fast, maintainable code.

Skills

Photon-efficient imaging

3D geometry

Probability

Statistics

Linear algebra

C++

Python

PyTorch

TensorFlow

Education

BSc/MSc in Computer Science, Electrical Engineering, or related field

Tools

PyTorch

TensorFlow

Job description

SNAP, Inc. in London is seeking a Computer Vision & Machine Learning Engineer to tackle challenges in ultra-low-light, high-temporal-resolution imaging for wearable AR devices.

You will design algorithms and models tailored for photon-efficient, event-driven imaging systems and collaborate across global teams. You will work on tracking, depth estimation, and SLAM, developing features for the next generation of AR glasses, while delivering fast, robust code and contributing to a strong CV/ML