Computer Vision Engineer

Develop, evaluate and improve Computer Vision and machine-learning solutions using the existing codebase and delivery approach.

Scope of Work

• Train, fine-tune and evaluate Computer Vision models
• Prepare and maintain datasets, experiments, evaluation results and model artefacts
• Investigate false detections, missed events, tracking errors and model degradation
• Identify edge cases, define labelling tasks and review annotation quality
• Analyse conditions such as layout, lighting, camera angle and crowding that may affect performance
• Support model packaging, versioning, deployment, release and rollback activities
• Perform retraining, threshold tuning and regression testing when required
• Maintain model documentation, evaluation reports, limitations and handover materials.
• Monitor model in production and maintain the model performance
• Follow organization's privacy, security, data-retention and AI-governance requirements

Minimum Required Experience and Qualifications

• Practical Python, deep-learning and Computer Vision experience
• Experience with at least one Computer Vision workflow such as detection, classification, tracking, pose estimation or video analytics
• Familiarity with frameworks such as PyTorch, TensorFlow, OpenCV or similar tools
• Understanding of dataset preparation, model training, precision, recall, F1 and latency
• Able to analyse model failures and recommend data, configuration or model improvements.
• Familiarity with annotation tools and labelling quality checks
• Good documentation and communication skills
• Experience with Docker, MLOps, experiment tracking, ONNX, TensorRT or GPU inference is useful but not mandatory
• Hospitality, F&B or camera-based analytics experience is useful but not mandatory