Computer Vision Engineer
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. The Company’s three core products are Snapchat , a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio , an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles . 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. The Spectacles team is looking for a Computer Vision Engineer to join the AR team at Snap inc! What you’ll do: 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 with the next generation of Snap’s wearable computing devices. Working from our London office, you will be collaborating closely with other Spectacles software and hardware teams around the world. Additionally you will:
- Develop and productise novel technologies for the next generation of wearable AR devices.
- Explore and advance state-of-the-art machine learning and computer vision algorithms.
- Develop and deploy machine learning models.
- Work together with our cross-functional engineering and research teams in computer vision, machine learning and AR engineering.
- Deep understanding in one of:
- Machine learning principles, solutions and frameworks to develop networks and models for computer vision tasks
- 3D computer vision principles, SLAM, VIO, or 3D localisation
- Ability to understand, debug and improve existing code as well as develop new algorithms using advanced computer vision and machine learning techniques.
- Strong communications and interpersonal skills.
- A genuine passion for learning new things and helping colleagues improve.
- Bachelor's Degree in a relevant technical field such as computer science or equivalent years of practical work experience
- Experience of post-Bachelor’s computer vision/machine learning experience; or Master’s degree in a technical field + experience of post-grad computer vision/machine learning experience; or PhD in a relevant technical field some experience of post-grad computer vision/machine learning experience
- One of:
- Experience in developing machine learning models for at least one of the following areas: 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.
- Msc/PhD in related field (Computer Vision, Machine Learning)
- Experience in integrating Machine Learning models into Augmented Reality solutions
- Experience in neural network optimization (pruning, quantization, distillation) to deploy efficient models to resource-constrained devices.
- Experience with software development in C++