Computer Vision ML Engineer — Production-Ready AI Systems

Exasoft; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Exasoft in Singapore seeks a Computer Vision / ML Engineer to develop and productionize Computer Vision and Machine Learning solutions.

You will train, evaluate, and refine models, prepare datasets, monitor performance in production, and support deployment, versioning, and documentation while adhering to privacy and governance requirements.

The role emphasizes data quality, experimentation, and collaboration with cross-functional teams to deliver robust, scalable AI capabilities.

Qualifications

• Proven hands-on experience with Python, deep learning and computer vision.
• Experience in CV tasks such as image classification, object tracking or video analytics.
• Strong understanding of ML performance metrics (precision, recall, F1, latency).

Responsibilities

• Train, fine-tune and evaluate computer vision and ML models.
• Prepare and maintain datasets, experiments, and evaluation results.
• Investigate false detections, missed events, tracking errors and model degradation.
• Identify data labelling requirements and review annotation quality.
• Analyze lighting, camera angles, layouts and crowding affecting model performance.
• Perform model retraining, threshold tuning and regression testing when needed.
• Support model packaging, versioning, deployment, release and rollback activities.
• Monitor models in production and maintain performance.
• Maintain technical documentation and handover materials.
• Ensure privacy, security, data-retention and AI-governance adherence.

Skills

Python

Deep learning

Computer Vision

PyTorch

TensorFlow

OpenCV

Education

Diploma or Degree in Computer Science, Artificial Intelligence, Data Science, Engineering

Tools

PyTorch

TensorFlow

OpenCV

Job description

Exasoft in Singapore seeks a Computer Vision / ML Engineer to develop and productionize Computer Vision and Machine Learning solutions.

You will train, evaluate, and refine models, prepare datasets, monitor performance in production, and support deployment, versioning, and documentation while adhering to privacy and governance requirements.

The role emphasizes data quality, experimentation, and collaboration with cross-functional teams to deliver robust, scalable AI capabilities.