AI/ML Ops Engineer — Databricks Pipelines & CI/CD

BSI Services Malaysia Sdn Bhd; Kuala Lumpur; Hybrid; MYR 140,000 - 210,000; Full time

Benefits offered by this job

Flexible working

16 days annual leave

Paid sick leave

Bank holidays

Group hospitalisation and surgical ins

Life insurance

Transport allowance

Internet/phone allowance

Paid maternity leave

Paid paternity leave

Paid marriage leave

Paid bereavement leave

Learning and development opportunities

Flexible benefits package

Job summary

BSI Services Malaysia Sdn Bhd is hiring an AI Engineer - ML Ops on a permanent, hybrid basis from Kuala Lumpur.

You will build, deploy and operate machine learning solutions on the Databricks platform, reporting to the Head of Data Platform and Services, and partnering with data science, data engineering and product teams to turn prototypes into production-grade pipelines that are reliable, secure and scalable.

Qualifications

• Proven experience delivering ML/Analytic solutions across data disciplines.
• Hands-on experience with Databricks or similar lakehouse platforms.
• Experience implementing MLOps across the model lifecycle (CI/CD, versioning, monitoring).
• Collaboration with security, governance, and risk teams to evidence controls.
• Strong Python packaging, Git, CI/CD, testing, and containerisation skills.

Responsibilities

• Design, build, and maintain end-to-end ML pipelines on Databricks.
• Develop production-grade Python and Spark solutions following best practices.
• Implement MLOps: MLflow, versioning, monitoring, and deployment governance.
• Build and maintain CI/CD pipelines for ML solutions with automated testing.
• Monitor production ML models and data pipelines for quality and drift.
• Collaborate with data engineering, data science, security and governance teams.

Skills

ML Engineer

MLOps

Python

Spark

Tools

Databricks

MLflow

Git

CI/CD

Spark

Job description

BSI Services Malaysia Sdn Bhd is hiring an AI Engineer - ML Ops on a permanent, hybrid basis from Kuala Lumpur.

You will build, deploy and operate machine learning solutions on the Databricks platform, reporting to the Head of Data Platform and Services, and partnering with data science, data engineering and product teams to turn prototypes into production-grade pipelines that are reliable, secure and scalable.