ML Engineer: Production AI & MLOps

AEON Bank; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

AEON Bank is seeking a Machine Learning Engineer to design, build, and operate production-grade ML and AI systems powering our digital banking platform.

You will work with Data Scientists, Data Engineers, Product Owners, and Software Engineers to transform models into scalable, secure services across our AI-driven platform. The role covers end-to-end lifecycle from data and model deployment to monitoring and continuous improvement.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI, Software Engineering or related quantitative field.
• 2–3+ years of experience in a machine learning role or related data science/engineering experience.
• Strong understanding of ML algorithms, feature engineering and model evaluation.
• Familiarity with LLMs, RAG or AI agent frameworks (Langchain, Langgraph, Pydantic AI) is a plus.
• Proficiency in Python and scripting languages (bash).
• Experience building ML pipelines (Airflow, Metaflow), experiment tracking (MLflow) and CI/CD.

Responsibilities

• Design, build, and operate production-grade ML/AI systems.
• Collaborate with Data Scientists, Data Engineers, Product Owners and Software Engineers to scale models into services.
• Develop end-to-end MLOps pipelines including deployment, monitoring, and model versioning.
• Architect secure, scalable cloud-native AI infrastructure using IaC and platform engineering best practices.
• Establish monitoring and drift detection to ensure reliability and performance.

Skills

Python

ML Engineering

MLOps

Cloud (AWS/Azure/GCP)

Docker/Kubernetes

Education

Bachelor's or Master's in CS/DS/AI

Tools

Docker

Kubernetes

MLflow

Airflow

Terraform

Job description

AEON Bank is seeking a Machine Learning Engineer to design, build, and operate production-grade ML and AI systems powering our digital banking platform.

You will work with Data Scientists, Data Engineers, Product Owners, and Software Engineers to transform models into scalable, secure services across our AI-driven platform. The role covers end-to-end lifecycle from data and model deployment to monitoring and continuous improvement.