About the Role
Develop, evaluate and improve Computer Vision and machine-learning solutions using the existing MBS codebase and delivery approach.
Scope of Work / Duties and Responsibilities
- 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 MBS 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