We're a venture backed, Series A startup developing a new method for physical access point authentication. Similar to FaceID on iPhone X, the technology unlocks spaces only when it identifies the person in front of it has access. To achieve this, we use facial detection and recognition, 3D sensing and artificial intelligence to enable highly secure and frictionless entry into physical locations.
You will ensure the quality, reliability, and safety of machine learning, computer vision and firmware-integrated software on a workstation and embedded device (product) level. You will be designing methods to automate manual test plans for regression and stability, gathering and parsing of logs to establish baselines and to analyze trends. You will be providing reporting mechanisms for analytics and automation of test pass/fail detection.
Apply by sending your resume to email@example.com