Computer Vision Engineer

Location: London, United Kingdom

Department: Spectacles

Employment Type: Full time

About Snap Inc

Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together.

About the Role

Snap Inc. is a camera company at heart, believing that the lens presents the greatest opportunity to improve how people live and communicate. We empower expression, presence, discovery, and fun through Snapchat, Lens Studio, and our pioneering Spectacles AR glasses. The Spectacles team is revolutionizing wearable AR with fifth-generation devices powered by Snap OS, blending see-through displays with advanced camera tech to make playing, learning, and working more immersive and connected. Join our London-based AR team as a Computer Vision Engineer, where you'll push the frontiers of machine learning and 3D vision to seamlessly merge real and virtual worlds on next-gen Spectacles. In this role, you'll develop cutting-edge CV/ML technologies tailored for lightweight AR wearables, optimizing algorithms like SLAM, VIO, and neural scene representations for real-time performance on battery-powered glasses. Collaborating with global software, hardware, and research teams, you'll productize innovations that leverage Spectacles' cameras for intuitive AR experiences— from geometric reconstruction to monocular depth sensing—enhancing Snap's creative ecosystem of visual messaging and augmented reality. We're seeking engineers with a deep passion for AR innovation and Snap's playful culture. You'll thrive in our 'default together' environment, working 4+ days a week in-office to spark dynamic ideas. Snap is an equal opportunity employer celebrating diverse backgrounds, with benefits like comprehensive health coverage, parental leave, mental health support, and equity in our mission to redefine human connection through camera-powered AR.

What You'll Do

• Develop and productize novel computer vision and machine learning technologies for next-generation Spectacles AR devices
• Explore and advance state-of-the-art machine learning and 3D computer vision algorithms for real-time AR experiences
• Develop and deploy efficient machine learning models optimized for wearable computing
• Collaborate with cross-functional teams in computer vision, machine learning, AR engineering, and hardware across global Snap locations
• Implement SLAM, VIO, and 3D localization systems to bridge real and virtual worlds via Spectacles' cameras
• Optimize algorithms for low-power, see-through AR glasses running Snap OS
• Debug and enhance existing CV/ML pipelines for seamless AR interactions
• Contribute to innovative camera-driven features that enhance play, learning, and collaboration in the real world
• Prototype and test computer vision solutions in Spectacles prototypes
• Stay ahead of AR trends to push boundaries in visual messaging and augmented reality
• Document and share technical insights to foster Snap's creative culture

Minimum Qualifications

• Bachelor's Degree in a relevant technical field such as Computer Science, Electrical Engineering, or equivalent practical work experience
• Post-Bachelor’s experience in computer vision or machine learning
• Master’s degree in a technical field plus post-grad experience in computer vision or machine learning, or PhD in a relevant technical field with some post-grad experience
• Experience developing machine learning models for geometric scene understanding, semantic scene reconstruction, neural scene representation, or monocular depth estimation
• Experience in geometric computer vision techniques such as SLAM, VIO, tracking, multi-view 3D reconstruction, or depth estimation
• Ability to understand, debug, and improve existing code, and develop new algorithms using advanced computer vision and machine learning techniques
• Strong communication and interpersonal skills with a passion for learning and helping colleagues improve

Preferred Qualifications

• MSc or PhD in Computer Vision, Machine Learning, or related field
• Experience integrating Machine Learning models into Augmented Reality solutions
• Experience in neural network optimization (pruning, quantization, distillation) for resource-constrained devices
• Experience with software development in C++
• Background in wearable AR hardware or camera-based technologies

Knowledge, Skills & Abilities

• Deep understanding of machine learning principles, frameworks, and models for computer vision tasks
• Expertise in 3D computer vision, including SLAM, VIO, and 3D localization
• Proficiency in developing and deploying ML models for scene understanding and depth estimation
• Experience with geometric computer vision techniques like tracking and multi-view reconstruction
• Strong programming skills in Python, C++, and AR frameworks
• Ability to optimize neural networks for edge devices (pruning, quantization)
• Debugging and algorithm development in resource-constrained environments
• Cross-functional collaboration in fast-paced AR/hardware teams
• Strong problem-solving for real-time camera and AR applications
• Excellent communication for technical and creative discussions
• Passion for AR innovation and Snap's camera-first mission
• Adaptability to wearable tech challenges
• Familiarity with Snap OS or similar AR platforms
• Interpersonal skills for global team synergy
• Continuous learning mindset in evolving CV/ML fields

Our Benefits

• Paid parental leave
• Comprehensive medical, dental, and vision coverage
• Emotional and mental health support programs
• Competitive compensation packages with equity to share in Snap’s long-term success
• Flexible PTO and wellness stipends
• Onsite perks including meals, fitness facilities, and creative spaces
• Professional development opportunities in AR and camera tech
• Inclusive community events celebrating Snap's diverse culture

"Default Together" Policy: At Snap Inc, we practice a "default together" approach and expect team members to work in an office 4+ days per week.

Snap is proud to be an equal opportunity employer.