Job
- Level
- Experienced
- Job Field
- Data, Embedded
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Vienna
- Working Model
- Hybrid, Onsite
Job Summary
In this role you develop robust SLAM and visual-tracking algorithms, implement efficient C++ for 3D reconstruction and camera calibration, improve non-linear optimization and Kalman filtering, and integrate real-time AR detectors.
Job Technologies
Your role in the team
As a Computer Vision Engineer on this team, you’ll work on solving some of our industry’s toughest challenges and develop the next generation of wearable devices.
Working from our Vienna office, you will be collaborating closely with other Snap hardware and software teams around the world.
- Contribute to state-of-the-art tracking / SLAM algorithms.
- Develop novel features for the next generation of AR products.
- Design, implement, and integrate existing and new Computer Vision and Augmented Reality algorithms.
- Research new techniques to improve speed and quality of existing algorithms for Computer Vision.
- Work with our computer vision team to deliver next-generation detection (such as face, hand, body etc.) technology for augmented reality systems.
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Our expectations of you
Qualifications
- Solid foundation in Computer Vision such as camera models, multi-view geometry and transformations.
- Solid math background with understanding of 3D geometry, trigonometry, and linear algebra.
- Ability to transform ideas into clean, fast and reliable code.
- Attention to detail, strong desire for quality and good communication skills.
- Outstanding problem solving skills.
- Track record of successful projects showing computer vision skills.
Experience
- BSc/MSc with 3+ years of relevant experience from industry in a relevant engineering discipline (e.g. computer science, mechatronics, mathematics, robotics, ...).
- Experience with SLAM or visual tracking systems.
- 3+ years of programming experience in C++.
- Masters, PhD, or industrial experience in a relevant engineering discipline.
- Experience with non-linear optimization, Kalman filtering, State-estimation.
- Experience in implementing high-performance computer vision algorithms.
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Job Locations
Topics that you deal with on the job
This is your employer
Snapchat
We believe that the camera is one of the most important tools for communication and self-expression. We are dedicated to creating new and innovative ways to improve the way people communicate and share their lives with others.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Internet, IT, Telecommunication
Dev Reviews
by devworkplaces.com
Total
(1 Review)Career Growth
3.4Workingconditions
4.6Engineering
2.7Culture
4.0
Computer Vision Engineer SLAM
- Location
- Vienna
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
