Machine Learning Engineer (12-Month Contract) - Lineman Wongnai

LINE MAN Wongnai is Thailand's leading provider of On-Demand Services, Merchant Digital Solutions, and Payment and Financial Services. We are seeking a Machine Learning Engineer for a 12-month contract to lead the migration of our machine learning and production model infrastructure to a modernized cloud environment. You will work directly with the Machine Learning Engineering and Data Science teams to re-platform existing training, serving, and feature data pipelines onto new cloud-native infrastructure. This is a hands-on execution role focused on the migration project, requiring the ability to ramp up quickly and contribute within the first few weeks. The role involves re-platforming the ML lifecycle, driving application integration, and ensuring production health during the transition.

The successful candidate will be responsible for migrating MLOps infrastructure, training pipelines, and CI/CD workflows, as well as migrating data and feature pipelines to ensure uninterrupted data flow. You will establish monitoring and incident response for data quality and model drift during the cutover. Post-migration, you will optimize system performance by troubleshooting bottlenecks and tuning models for latency and cost efficiency. The role requires a pragmatic engineering approach to deliver against a fixed scope and timeline while ensuring a clean handover of documentation and ownership to the full-time team.

• Re-platform the ML Lifecycle by migrating existing MLOps infrastructure, training pipelines, and CI/CD deployment workflows onto the new cloud environment's managed ML services.
• Drive Application Integration by migrating APIs, microservices, and backend business logic connecting ML models to downstream applications while maintaining prediction-serving SLAs.
• Migrate Data & Feature Pipelines by re-platforming data pipelines and feature stores onto the new cloud environment to ensure continuous data flow for training and inference.
• Own Production Health & Observability During Cutover by establishing monitoring, anomaly detection, and incident response for data quality, model drift, and A/B testing performance.
• Optimize System Performance Post-Migration by troubleshooting production bottlenecks and tuning models for latency, throughput, and compute cost efficiency.
• Document & Hand Over by producing migration runbooks and architecture documentation and transferring ownership of migrated systems to the full-time team.

• 3+ years of professional experience in software engineering, machine learning engineering, or data science with the ability to work independently from day one.
• Working knowledge of core ML concepts and frameworks including PyTorch, TensorFlow, or Scikit-Learn to validate migrated models and pipelines.
• Strong proficiency with Python or Go in production environments, with exposure to distributed computing frameworks like Apache Spark considered a plus.
• Solid understanding of systems architecture and distributed systems to maintain and re-platform complex ML pipelines and application logic against a defined timeline.
• Prior experience migrating infrastructure or workloads between environments (on-prem to cloud, or cloud to cloud) is a strong plus.
• Practical understanding of how MLOps pipelines interlock end to end to trace and move all dependencies during migration.
• A pragmatic, high-velocity engineering approach comfortable delivering against a fixed scope and timeline.

• Hands-on experience with major cloud platforms' ML and data services such as AWS SageMaker, Glue, and EKS, GCP Vertex AI, or Azure ML.
• Experience with container orchestration tools like Kubernetes or workflow orchestration tools like Apache Airflow for managing scalable ML workloads.