Computer Vision Architect, Manager - Applied Artificial Intelligence (26127)
- Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based as well as client-owned platforms
- Deploy automation and cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
- Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements
- 6+ years of relevant work experience
- 2+ years of experience leading and managing project teams
- 2+ full cycle product experiences (prototype to production) deploying computer vision solutions
- API development experience
- Bachelor's Degree
- Travel up to 50% of the time (Monday - Thursday/Friday) (While 50% of travel is a requirement of the role, due to COVID-19, non-essential travel has been suspended until further notice.)
- Advanced Degree preferably in applied mathematics, statistics, computer science, data science, electrical engineering, physics, or closely related field
- Formal training in one or many of the following: computer vision, image processing, linear and non-linear programming, machine learning, linear algebra
- Certification or expertise on at least one of the following platforms: Google Vision, AWS Rekognition, Azure Computer Vision/Face/Content Moderator, or Watson Visual Recognition
- Expertise in computer vision or deep learning frameworks and libraries, e.g. PyTorch, OpenCV, Keras, Tensorflow, scikit-image
- Advanced skills in Python
- Strong knowledge of machine learning, deep learning, image processing, computer vision
- Experience with quantitative modeling (design, development & implementation) using 3+ types of algorithms (e.g., YOLOv3, RetinaNet, Faster R-CNN)
- Expertise in fields e.g. structured information extraction, object detection, action recognition, image segmentation, spatiotemporal modeling (hybrid CNN/RNN)
- Ability to work independently, manage small engagements or parts of large engagements.
- Strong oral and written communication skills, including presentation skills (MS Visio, MS PowerPoint).
- Strong problem solving and troubleshooting skills with ability to exercise mature judgment.