II
Posted:
March 03, 2026
Location:
Kuala Lumpur, Kuala Lumpur, Malaysia
Job Description
Hands-on experience on end-to-end model deployment on Azure is critical — candidates with hands-on model development and maintenance experience, ideally with AzureML
- Experience of develop and deploy propensity models.
Job Description
• Design, build, and maintain robust machine learning models into AzureML.
• Develop reusable components for model training, evaluation, and deployment.
• Monitor model performance in production and implement automated retraining workflows.
• Optimize models for accuracy, latency, scalability, and cost efficiency.
• Collaborate with data scientists to productionize experimental models using best engineering practices.
Skills/ Experience
• Strong programming skills in Python and familiarity with ML frameworks (lightBoost, sklearn).
• Solid understanding of model evaluation, drift detection, and monitoring techniques.
• Experience in building and maintaining CI/CD pipelines for ML (e.g., MLflow, Kubeflow, Airflow, SageMaker...
- Experience of develop and deploy propensity models.
Job Description
• Design, build, and maintain robust machine learning models into AzureML.
• Develop reusable components for model training, evaluation, and deployment.
• Monitor model performance in production and implement automated retraining workflows.
• Optimize models for accuracy, latency, scalability, and cost efficiency.
• Collaborate with data scientists to productionize experimental models using best engineering practices.
Skills/ Experience
• Strong programming skills in Python and familiarity with ML frameworks (lightBoost, sklearn).
• Solid understanding of model evaluation, drift detection, and monitoring techniques.
• Experience in building and maintaining CI/CD pipelines for ML (e.g., MLflow, Kubeflow, Airflow, SageMaker...
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Job Type:
Full-time
Location:
Kuala Lumpur, Malaysia
Posted:
March 03, 2026
Deadline:
April 12, 2026