Senior AI Data Engineer: ML in Production & Data Pipelines

Axiom; Seberang Perai; On-site; MYR 180,000 - 300,000; Full time

Benefits offered by this job

Medical benefits, dental, vision

Life Insurance

Paid Time Off

Performance Bonus

Job summary

Axiom is seeking an AI Data Senior Engineer to join our Batu Kawan, Penang team to help design, build, and deliver data solutions for AI workloads. You will develop ETL pipelines, manage backend integrations, and enable production ML deployments with clean, reliable data.

The role requires strong skills in SQL, Python, Spark, Hadoop, and Kafka, plus experience with cloud data services like AWS Redshift, Azure Data Factory, and GCP BigQuery.

Qualifications

• Bachelor’s in Computer Science, Information Systems, or related field.
• 4–6 years in data engineering with ETL pipeline development and backend integration.
• Experience supporting AI/ML workflows with clean, reliable data.
• Proven track record deploying ML models in production environments.
• Strong problem-solving and analytical mindset.
• Ability to work independently or collaboratively in teams.
• Strong programming and coding discipline across multiple languages.
• Excellent communication and presentation skills to technical and non-technical audiences.

Responsibilities

• Work on AI data platforms and data pipelines to support ML workflows.
• Develop and maintain ETL pipelines and backend integrations.
• Deploy ML models in production environments and monitor performance.
• Collaborate with cross-functional teams to ensure data quality and governance.

Skills

AI/ML workflows

SQL

Python

Spark

Hadoop

Kafka

Education

Bachelor’s in Computer Science or related field

Tools

AWS Redshift

Azure Data Factory

GCP BigQuery

Job description

Axiom is seeking an AI Data Senior Engineer to join our Batu Kawan, Penang team to help design, build, and deliver data solutions for AI workloads. You will develop ETL pipelines, manage backend integrations, and enable production ML deployments with clean, reliable data.

The role requires strong skills in SQL, Python, Spark, Hadoop, and Kafka, plus experience with cloud data services like AWS Redshift, Azure Data Factory, and GCP BigQuery.