CLEAR’s mission is to strengthen security and create frictionless experiences. We believe you are you and by using your biometrics – your eyes, face, and fingerprints – we keep you moving. Imagine a world where you can do virtually everything you need to – breeze through the airport, buy a beer at the game, check-in at the doctor’s office, access your office building, and more – without ever pulling out your wallet. CLEAR is currently available in 50+ airports, stadiums and venues nationwide. Now with Health Pass, CLEAR securely connects a person’s digital identity to multiple layers of COVID-related insights to help reduce public health risk and restore peace of mind.
We’re defining and leading an entirely new industry, obsessing over our customers, and investing in great people to lead the way. Recently named on CNBC’s Disruptor 50 List for the second year in a row and winner of the SXSW Interactive Innovation Award, CLEAR is providing innovative technology options for businesses and our 5+ million members to help create a safer environment no matter where you go.
CLEAR is seeking a Research Software Engineer to join our team. Your work will directly contribute to advancements in the field of human-computer interaction. You will be responsible for measuring and helping drive data-driven improvement of biometric matching accuracy, evaluation of biometric sensors, sourcing and assembling test apparatus, developing experiments, collecting data, and data analysis. The ideal candidate should be comfortable with creative problem solving in a late-stage startup environment. If you like tinkering, are curious by nature, and/or consider yourself a technologist or an innovator, this may be the role for you.
What You Will Do:
- Explore novel imaging technologies (2D/3D) for face image capture in order to foster the growth of our platform.
- Establish and maintain CLEAR-wide best practices in image capture and performance evaluation.
- Design and run experiments to evaluate the performance of new capture devices, control algorithms, biometric algorithms and user workflows.
- Establish a model of sample utility to optimize face image capture across applications.
- Develop a scalable module to continuously monitor performance of CLEAR’s exponentially growing biometrics systems
Who You Are:
- Background in statistics, machine learning, computer vision, biometrics, robotics and/or imaging and have completed a software project in at least one of these areas.
- Must also possess software engineering experience & familiarity with one of the following technologies: Java, Python, C++, C#
- Must be experienced in at at least one field: R&D in computer vision, R&D in image processing, statistical modeling & analysis
- Experience in machine learning & computer vision packages such as openCV, etc. is desirable
- Ability to break down scientific results to product security and usability aspects.
- Analytical and scientifically rigorous.