Computer Vision Engineer

Responsibilities Explore our data and workflows to identify opportunities where CV/ML-based solutions can have the most impact Apply classical computer vision techniques — feature matching, geometric transformations, image registration — to build internal and customer-facing features Prepare training data, and train, fine‑tune, and validate vision‑based models Develop cross‑technology solutions that combine VLMs, vision‑based models, and classical CV to solve problems no single approach can Ship CV pipelines that can be continuously monitored and validated, with evaluation harnesses and quality metrics built in from day one Requirements 3 years of experience building computer vision systems in Python, with tools such as OpenCV, NumPy, and PyTorch (or equivalents) Solid grounding in classical computer vision: feature extraction and matching, geometric transformations, image registration, and robust estimation (e.g., RANSAC) Solid grounding in ML and ML‑based computer vision: CNNs, transformers, embedding spaces Hands‑on experience preparing datasets and training, fine‑tuning, and evaluating vision‑based models Start‑up ready: autonomous, moves fast, takes initiative without being asked Strong verbal and written communication, able to articulate ideas clearly and collaborate effectively A degree in Computer Science, Electrical Engineering, or a related field (B.S. or M.S.) #J-18808-Ljbffr Jobtailor