Computer Vision Engineer

<div><strong>Computer Vision Engineer — Perception &amp; 3D</strong><br><strong>Type:</strong> Temporary<br>&nbsp;<strong>Duration:</strong> 6–12 months<br><strong>What You'll Gain</strong></div> <ul> <li>Exposure to the full CV pipeline, from raw data and annotation to deployed model</li> <li>Mentorship from CV engineers working on production systems</li> <li>Hands-on experience with YOLO, PyTorch, 3D reconstruction, and modern perception workflows</li> <li>Concrete portfolio work — datasets, scripts, reconstructions, and model contributions — that translates directly to future ML/CV roles</li> </ul> <div><strong>What You'll Do</strong></div> <ul> <li>Annotate and QA images and video for detection, segmentation, and classification — and build the tooling to do it at scale</li> <li>Work on 3D reconstruction (photogrammetry, Gaussian splatting) and explore applications in AR/VR and autonomy</li> <li>Write Python tooling to convert annotation formats, validate label integrity, and generate dataset statistics</li> <li>Help shape labeling schemas and class taxonomies as edge cases arise</li> <li>Run baseline YOLO training experiments to evaluate dataset quality and surface labeling gaps</li> <li>Document conventions and edge-case decisions</li> </ul> <div><strong>Required</strong></div> <ul> <li>Recent graduate with a degree in CS, EE, AI/ML, or related field</li> <li>Working knowledge of Python and common CV libraries (NumPy, OpenCV)</li> <li>Attention to detail and patience for precision work</li> </ul> <div><strong>Nice to Have</strong></div> <ul> <li>Hands-on experience with YOLO or PyTorch</li> <li>Familiarity with 3D reconstruction, segmentation masks, or model-assisted labeling workflows</li> <li>Interest in AR/VR, SLAM, or autonomous systems</li> </ul>