ML Engineer: Computer Vision & Production Deployments

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD is seeking a Computer Vision/MLOps professional in Singapore to train, fine-tune, and evaluate models, preparing datasets, experiments, and artefacts for production readiness.

You will diagnose failures, optimize performance under varying conditions, and ensure robust labeling quality. Experience with PyTorch/TensorFlow, OpenCV, and Docker is preferred, with strong documentation skills.

Qualifications

• Practical Python, deep-learning and Computer Vision experience.

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 privacy, security, data-retention and AI-governance requirements.

Skills

Python

Deep learning

Computer Vision

PyTorch

TensorFlow

OpenCV

Docker

MLOps

Experiment tracking

ONNX

TensorRT

GPU inference

Tools

Docker

ONNX

TensorRT

Job description

OPTIMUM SOLUTIONS (SINGAPORE) PTE LTD is seeking a Computer Vision/MLOps professional in Singapore to train, fine-tune, and evaluate models, preparing datasets, experiments, and artefacts for production readiness.

You will diagnose failures, optimize performance under varying conditions, and ensure robust labeling quality. Experience with PyTorch/TensorFlow, OpenCV, and Docker is preferred, with strong documentation skills.