Senior AI/ML Engineer – Cloud Data Pipelines & MLOps

Axonect; Kuala Lumpur; Vor Ort; MYR 180.000 - 280.000; Vollzeit

Zusammenfassung

Axonect is seeking an experienced ML/Sofware Engineer in Kuala Lumpur to develop and deploy AI/ML solutions in enterprise settings. You will build data pipelines, manage ML workloads, and collaborate across cross-functional teams in an Agile environment.

You should have a solid background in ML, Python, SQL, Airflow, Snowflake, and Git, with hands-on experience deploying end-to-end ML projects and strong SDLC practices.

Qualifikationen

• Bachelor's degree in Computer Science, Information Technology, or related field.
• Minimum 4 years of experience in Machine Learning, Software Development.
• Hands-on experience developing and deploying AI/ML solutions in enterprise environments.
• Experience working in Agile/Scrum development teams.

Aufgaben

• Develop and maintain AI/ML solutions using Python and relevant ML frameworks.
• Build and manage data pipelines using Airflow and Snowflake/Snowpark.
• Perform data processing, transformation, validation, and analysis using SQL.
• Develop scripts and automation using CLI/Bash.
• Deploy and support ML workloads using Azure ML.
• Manage source code using Git and follow software development best practices.
• Support model deployment, monitoring, and operationalization.
• Collaborate with data scientists, testers, and business teams to deliver ML use cases.
• Support MLOps, CI/CD, and containerization activities where required.

Kenntnisse

Machine Learning

Python

Data analysis

Problem solving

Stakeholder management

Ausbildung

Bachelor's degree in Computer Science or related field

4+ years in ML/Software Development

Tools

Airflow

Snowflake/Snowpark

SQL

Git

Azure ML

CI/CD

Docker

Jobbeschreibung

Axonect is seeking an experienced ML/Sofware Engineer in Kuala Lumpur to develop and deploy AI/ML solutions in enterprise settings. You will build data pipelines, manage ML workloads, and collaborate across cross-functional teams in an Agile environment.

You should have a solid background in ML, Python, SQL, Airflow, Snowflake, and Git, with hands-on experience deploying end-to-end ML projects and strong SDLC practices.