ML Engineer in Yangon

ML Engineer

(Business Analyst)

CB Bank

Botahtaung | Yangon

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ML Engineer

ML Engineer

CB Bank

APPLY HERE

ML Engineer

(Business Analyst)

CB Bank

Myanmar - Yangon

Botahtaung | Yangon

1 week ago

APPLY HERE

Experience level

Experienced Non-Manager

Job Function

IT Hardware, Software

Job Industry

Banking/ Insurance/ Microfinance

Min Education Level

Bachelor Degree

Job Type

Full Time

Job Description

A Fantastic Opportunity for ...

Design, build, and maintain the infrastructure and tools required to train, deploy, and monitor machine learning models at scale.
Collaborate with Data Scientists to productionize ML models, ensuring reliability, security, and performance.
Implement MLOps practices including CI/CD pipelines, automated retraining, model versioning, and monitoring.
Work within the Microsoft Azure ecosystem (Azure ML, Databricks, Synapse, Data Lake, Fabric) to support AI/ML workloads.
Optimize models for scalability and latency in production environments.
Build and manage feature stores and model registries to streamline AI development.
Integrate AI models with enterprise systems (APIs, Power BI, Microsoft 365 apps).
Develop monitoring dashboards to track model drift, accuracy, and performance.
Partner with Data Engineers to ensure robust data pipelines feed into ML models.
Document processes and ensure compliance with data governance, privacy, and auditability requirements.
Stay up to date on emerging ML engineering and cloud technologies to improve operational efficiency.

Open To

Male/Female

Job Requirements

Proven experience as an ML Engineer, Data Engineer with ML focus, or MLOps Specialist.
Hands-on expertise with Azure ML, Azure Data Factory, Databricks, Synapse, and Data Lake.
Strong programming skills in Python (PyTorch, TensorFlow, MLflow, scikit-learn).
Proficiency in SQL and experience with databases (PostgreSQL, Oracle, MSSQL).
Experience with Pentaho Data Integration is a plus.
Solid understanding of MLOps pipelines (CI/CD, containerization with Docker/Kubernetes, GitHub Actions/Azure DevOps).
Knowledge of cloud deployment strategies (REST APIs, microservices, serverless functions)
Experience in monitoring tools for model performance, data drift, and reliability.
Familiarity with data governance and responsible AI frameworks.
Strong collaboration skills to work with Data Scientists, Engineers, and Business Stakeholders.
Excellent problem-solving and troubleshooting skills in production environments
Growth mindset, with ability to learn and adapt quickly in a fast-paced setting.