Opportunity brief

Responsibilities

Develop Computer Vision solutions using Python and OpenCV.
Work with YOLO / Ultralytics and other deep learning-based Computer Vision models.
Prepare, clean, organize, and annotate image/video datasets.
Train, fine-tune, validate, and evaluate Computer Vision models.
Work with object detection, classification, tracking, recognition, OCR, and video analytics.
Build image and video processing pipelines for real-world applications.
Work with CCTV footage, RTSP streams, and real-time video processing.
Research and experiment with different Computer Vision techniques, models, papers, and open-source implementations.
Develop Proofs of Concept (POCs) to test new ideas and approaches.

Model Evaluation & Optimization

Evaluate models using metrics such as:
Precision
Recall
mAP
F1 Score
IoU
Perform error analysis and identify reasons behind false positives and false negatives.
Improve model performance through better datasets, training strategies, parameters, and model selection.
Analyze real-world model performance rather than relying only on training metrics.
Experiment with different image sizes, augmentations, models, and inference approaches.

Integrate trained AI models into Python-based applications and APIs.
Work with frameworks such as Flask or FastAPI where required.
Develop and debug AI inference pipelines.
Work with databases and backend systems when required.
Assist in deploying Computer Vision solutions in real-world environments.
Optimize AI pipelines for performance, reliability, and scalability.
Work with technologies such as Docker, Linux, cloud platforms, CUDA, ONNX, or TensorRT when applicable.

Research technical problems independently before seeking help.
Read documentation, papers, GitHub repositories, and technical resources to understand possible solutions.
Compare different approaches and explain why a particular solution was selected.
Build small experiments and POCs to validate ideas.
Troubleshoot model and pipeline issues systematically.
Document experiments, findings, and technical decisions.