[Remote] Computer Vision Pipeline Engineer

Note: The job is a remote job and is open to candidates in USA. EAIGLE is an end-to-end AI platform transforming operations in the supply chain and logistics sectors through intelligent video and sensor data. The role involves building production computer vision systems that process real-world images and video at scale, owning the end-to-end vision pipeline from ingestion to delivery. Responsibilities • Design and build image/video CV pipelines (ingestion → preprocessing → inference → post-processing) • Deploy and operate computer vision models in production • Optimize pipelines for latency, throughput, and cost (GPU/CPU tradeoffs) • Work with video streams (RTSP, files, cameras) and real-world data quality issues • Implement model versioning, monitoring, and feedback loops • Collaborate with backend and platform engineers on APIs and infrastructure Skills • 3+ years building production computer vision or ML systems • Strong experience with Computer Vision (object detection, classification, tracking, OCR, etc.) • Hands-on experience with OpenCV, PyTorch or TensorFlow • Experience deploying models as services or pipelines • Comfortable with Docker, APIs, and cloud environments • Able to debug real-world CV failures (lighting, angles, false positives) • Must be based in Ontario, Canada • Must be legally eligible to work in Canada (no sponsorship required) • Experience with video analytics or edge AI • GPU inference optimization (TensorRT, CUDA, etc.) • Background in logistics, robotics, surveillance, or industrial CV • Experience working in startup or product-focused teams Benefits • A competitive compensation package, including base salary and stock options. • The opportunity to work in a startup environment, where your contributions directly impact the company’s growth and success. • A remote-first work environment with flexibility and autonomy. Company Overview • We help your enterprise leverage AI-powered vision data to address security, transportation, and operational challenges. It was founded in 2018, and is headquartered in Markham, Ontario, CAN, with a workforce of 11-50 employees. Its website is Apply tot his job