Computer Vision Professional

Job description

Educational Requirements Bachelor of Engineering Service Line Topaz COE unit Responsibilities - Assist in building and testing CV models for detection, tracking, classification tasks and latest foundation and VLM models. - Prepare and annotate image/video datasets, support data ingestion and cleaning pipelines - Contribute to writing and debugging training scripts, model loaders, and preprocessing functions - Run evaluation jobs and generate performance reports using tools like TensorBoard or custom scripts - Support error analysis by identifying model weaknesses across edge cases - Collaborate with senior engineers on integrating models into scalable inference pipelines - Help visualize model outputs, draw bounding boxes, heatmaps, or segmentation masks for explainability - Document experiments and code for reproducibility and knowledge sharing - Used OpenCV, MediaPipe, and scikit-image for preprocessing, motion analysis, and visual overlays - Integrated DL models with post-processing logic (e.g., NMS, temporal smoothing, event triggering) - Ensured low-latency inference by profiling and tuning frame-wise preprocessing - Supported integration of RTSP video feeds and video decoders in test pipelines - point-cloud ingestion and processing (Open3D/PCL), calibration/registration (ICP/FGR), 3D detection/segmentation with sparse CNNs/PointNet, and RGBLiDARIMU fusion Additional Responsibilities - Basic understanding of synthetic data or 3D asset usage in training pipelines - Familiarity with Git, Linux command line, and Jupyter Notebooks - Interest in building a career in computer vision and AI for real-world automation - Bachelors degree in Computer Science, Data Science, or a related technical field - 13 years of experience or strong internship/projects in computer vision or ML model development Technical and Professional Requirements - Good Python skills and working knowledge of PyTorch or TensorFlow - Familiarity with image processing libraries (e.g., OpenCV, PIL) and dataset tools (e.g., COCO format, YOLO datasets) - Eagerness to learn, take feedback, and contribute in collaborative development environments - Exposure to object detection/tracking projects (academic, hackathons, or prior work) Preferred Skills - Technology->AI-Data science->Computer Vision - Technology->AI-Generative AI->Generative AI - Basic - Technology->AI-Generative AI->Generative AI for Data Analytics