Computer Vision Engineer

Optimum Solutions Pte Ltd; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

Optimum Solutions Pte Ltd in Singapore is seeking a skilled Computer Vision and ML engineer to develop, evaluate, and refine CV solutions within our existing codebase and delivery framework. You will train and fine-tune CV models, prepare datasets and artefacts, investigate failures and edge cases, and contribute to model packaging, deployment, and governance.

Strong Python and DL fundamentals are essential, with hands-on experience in PyTorch/TensorFlow and Docker helping you thrive in this

Qualifications

• Practical Python, deep-learning and Computer Vision experience.
• Experience with at least one CV 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

Responsibilities

• Develop, evaluate and improve Computer Vision and ML solutions using the existing codebase and delivery approach.
• Train, fine-tune and evaluate CV models.
• Prepare and maintain datasets, experiments, evaluation results and model artefacts.
• Investigate false detections, missed events and tracking errors.
• Identify edge cases, define labelling tasks and review annotation quality.
• Analyse conditions affecting performance such as layout, lighting and camera angle.
• Support model packaging, versioning, deployment and rollback activities.
• Perform retraining, threshold tuning and regression testing when required.
• Maintain model documentation, evaluation reports and handover materials.
• Monitor model in production and maintain performance.
• Follow privacy, security, data-retention and AI-governance requirements.

Skills

Python

Deep learning

Computer Vision

Model evaluation

Data analysis

Documentation

Annotation quality checks

Experiment tracking

GPU inference

Tools

PyTorch

TensorFlow

OpenCV

Docker

ONNX

TensorRT

Job description

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