Snap Inc.

London
5,000 Total Employees
Year Founded: 2011

Snap Inc. Offices

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Our “default together” approach is an 80/20 model where we are asking team members to spend 80% of the time, on average, in the office, with the remaining 20% of the time spent remote.

Typical time on-site: 4 days a week

Global Office Locations

London

London, United Kingdom

Recently posted jobs

20 Days AgoSaved
Hybrid
London, Greater London, England, GBR
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Develop machine learning models and computer vision algorithms for photon-efficient, event-driven imaging in AR glasses. Responsibilities include tracking, depth estimation, SLAM, detection, probabilistic modeling, and novel imaging algorithms for ultra-low-light, high-temporal-resolution systems. The role requires collaboration with global hardware and software teams and emphasizes fast, reliable implementation in C++ and Python.
20 Days AgoSaved
Hybrid
London, Greater London, England, GBR
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Develop and deploy computer vision and machine learning algorithms for photon-efficient, event-driven imaging in next-generation AR glasses. Responsibilities include tracking, depth estimation, SLAM, detection, probabilistic modeling, and ultra-low-light imaging. The role requires close collaboration with global hardware and software teams and focuses on creating fast, robust, and accurate solutions for wearable devices.
25 Days AgoSaved
Hybrid
London, Greater London, England, GBR
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Build, deploy, and maintain machine learning models for Snapchat products. Apply ML techniques to real-world problems, contributing across data analysis, training, evaluation, and production deployment. Collaborate with cross-functional teams to launch scalable ML-driven features using modern AI tools and engineering workflows while maintaining high standards for correctness, security, and production quality.