Video Analytics Engineer

Responsibilities

• Build, develop and deploy image classification, object detection, video understanding, and imagery analysis services.
• Develop services to perform contextual scene analysis for understanding the functional relationships between objects. Current AI/ML methods allow for the accurate detection and tracking of people and objects in video frames. We seek to expand the current state-of-the-art to infer functional relationships between detected objects and people.
• Explore novel AI/ML model development for video analysis in areas including self-supervised learning, anomaly detection, multi-sensor fusion and spatio-temporal algorithms for dynamic object tracking.

Skills Required:

• US Citizens Only
• Past successful experience in applying machine learning and deep learning to solve computer vision and/or video analysis problems.
• Ability to work with complex problems.
• Strong coding skills. Experience with Python, C/C++ a plus
• Strong background in statistics. A minor in mathematics or statistics is a plus.
• AI/ML model optimization for scalable systems. Techniques for reducing computational resources of video analytics models such as binarization, pruning, and merging multiple pre-trained models – will be investigated to enable deployment of advanced video pipelines on minimal hardware resources. Solutions will be benchmarked in an Enterprise surveillance environment.
• Computer Vision, Machine Learning, or Data Science coursework or experience required.

Equitus Corp is an equal opportunity employer and does not discriminate against persons based on race, religion, national origin, sexual orientation, gender, gender identity and expression, marital status, age, disability, pregnancy, medical condition, or covered veteran status.