Most computer vision systems stop at object detection. We’re working on the harder challenge of understanding context, relationships, and behavior across video in real-world environments. If that’s the kind of perception work you like solving, I’d like to talk. Opportunity for a strong Computer Vision / ML Engineer interested in helping solve a challenging perception problem. This is not a typical CRUD SaaS problem Ideal experience includes: • Computer vision / AI-ML model development • Python, PyTorch, and OpenCV • Object detection, segmentation, pose estimation, and multi-object tracking • Video understanding and spatiotemporal analysis • Fine-tuning and evaluating open-source vision models • C++ and/or C# for production computer vision systems • Real-time inference, model optimization, or edge deployment is a plus A great fit would be engineers who enjoy taking difficult perception problems from model → experiment → measurable performance → production system. If this sounds like your area of expertise, or you know someone who may be interested, fill out the form below or share this link: Computer Vision / ML Engineer
[Hiring] Computer Vision / ML Engineer - Video Understanding, Tracking, Pose & Spatial Reasoning
A company is hiring a Computer Vision / ML Engineer to work on video understanding, tracking, pose estimation, and spatial reasoning, according to a job posting. The role requires experience with Python, PyTorch, and OpenCV, plus object detection, segmentation, pose estimation, and multi-object tracking, with C++ and/or C# for production computer vision systems; real-time inference, model optimization, or edge deployment is listed as a plus. The posting states the work is not a typical CRUD SaaS problem and seeks engineers who can take perception problems from model to experiment to measurable performance to production system.
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