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Computer Vision Engineer
Cannocksnap
- London, England, United Kingdom
- London, England, United Kingdom
Über
The Spectacles team is pushing the boundaries of technology to bring people closer together in the real world. Our fifth‑generation Spectacles, powered by Snap OS, showcase how standalone, see‑through AR glasses make playing, learning, and working better together.
Computer Vision Engineer – AR In this role, you will be working on state‑of‑the‑art machine learning and 3D computer vision technologies to straddle the boundaries between the real and the virtual world on the next generation of Snap’s wearable AR devices. Working from our London office, you will collaborate closely with Spectacles software and hardware teams worldwide.
What You’ll Do
Develop and productise novel technologies for wearable AR devices.
Explore and advance state‑of‑the‑art machine learning and computer vision algorithms.
Develop and deploy machine learning models.
Collaborate with cross‑functional engineering and research teams in computer vision, machine learning, and AR engineering.
Knowledge, Skills & Abilities
Deep understanding in machine learning principles, solutions, and frameworks for computer vision.
Deep understanding in 3D computer vision principles (SLAM, VIO, 3D localisation).
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.
A genuine passion for learning new things and helping colleagues improve.
Minimum Qualifications
Bachelor’s Degree in computer science or a related technical field, or equivalent practical experience.
Post‑bachelor experience in computer vision/machine learning; or master’s/PhD in a technical field with post‑grad experience; or PhD with some post‑grad experience.
Experience developing machine learning models for at least one of: geometric scene understanding, semantic scene reconstruction, neural scene representation, monocular depth estimation, visual localisation.
Experience in geometric computer vision such as SLAM, VIO, tracking, multi‑view 3D reconstruction, depth estimation, etc.
Preferred Qualifications
Master’s or PhD in computer vision or machine learning.
Experience integrating machine learning models into augmented reality solutions.
Experience with neural network optimisation (pruning, quantisation, distillation) for resource‑constrained devices.
Experience in C++ software development.
Accommodation available for applicants with disabilities.
Default Together Policy At Snap Inc., we believe that working in person helps build our culture faster. We expect team members to work in the office 4+ days per week.
Equal Opportunity Employer Snap is proud to be an equal‑opportunity employer, providing employment opportunities regardless of race, colour, religious creed, national origin, ancestry, disability, gender, sexual orientation, etc. EOE, including disability/veterans.
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Sprachkenntnisse
- English
Hinweis für Nutzer
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