Production AI Engineer – Vision & MLOps Expert

TNG Digital Sdn Bhd; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

TNG Digital Sdn Bhd in Kuala Lumpur, Malaysia is seeking a technically strong AI Engineer to maintain, optimize, and evolve our production AI ecosystem. You will focus on computer vision and applied AI use cases across domains, ensuring health, retraining, and reliability of deployed models and pipelines.

You will collaborate with AI Ops, solution architects, and data engineering to sustain a robust, traceable production environment that aligns with governance standards and internal AI policies.

Qualifications

• Proficient in Python with hands-on experience in ML frameworks (TensorFlow, PyTorch).
• Strong understanding of data pipelines for unstructured and structured data.
• Familiar with CI/CD workflows and model lifecycle management in production.

Responsibilities

• Monitor production AI systems for accuracy drift and reliability.
• Manage model retraining cycles with data updates, validation, and redeployment via automated CI/CD pipelines.
• Maintain and enhance data pipelines for image, video, and multimodal inputs.
• Fine-tune production models using TensorFlow or PyTorch.
• Automate evaluation and reporting with dashboards to monitor system health.
• Collaborate with AI Ops and Data Engineering for versioning and governance.
• Support small-scale enhancements and ensure production-readiness and compliance.

Skills

Python

TensorFlow

PyTorch

CI/CD

SQL

Git

MLOps

Model governance

Data pipelines

Tools

MLflow

Weights & Biases

Kubeflow

ONNX

TensorRT

TFLite

Job description

TNG Digital Sdn Bhd in Kuala Lumpur, Malaysia is seeking a technically strong AI Engineer to maintain, optimize, and evolve our production AI ecosystem. You will focus on computer vision and applied AI use cases across domains, ensuring health, retraining, and reliability of deployed models and pipelines.

You will collaborate with AI Ops, solution architects, and data engineering to sustain a robust, traceable production environment that aligns with governance standards and internal AI policies.