This position is 12 Months contract + extension based on performance and client's satisfaction
Work Location: Nakhon Ratchasima
SCOPE OF WORK
- Provide qualified Factory AI/ML Integration Developer staff to support Factory IT requirements for AI/ML application integration, factory data integration, model deployment, data/API integration, Factory MLOps platform support, and production software support.
- Develop, enhance, test, deploy, troubleshoot, document, and support software components required to integrate AI/ML solutions with factory systems.
- The scope includes model deployment support, API integration, data pipeline development, database integration, automation scripting, CI/CD support, containerized deployment support, production troubleshooting, and technical documentation.
- Work with IT Team, Factory Integration, Factory Engineering, Machine Development, Data Science, and production support teams to deliver and sustain AI/ML-enabled factory solutions.
Deliver and support the following work products as assigned by IT Team:
- Developed, tested, and documented software components for Factory AI/ML integration and MLOps platform support.
- Model deployment, API integration, data pipeline, database integration, and automation components.
- Troubleshooting and resolution of assigned development, deployment, integration, or production support issues.
- Technical documentation, deployment notes, troubleshooting guides, and knowledge transfer materials.
- Source code, configuration files, scripts, and related technical artifacts maintained in team-approved repositories or approved storage locations.
- Regular status updates, issue updates, risk escalation, and progress reporting as required by IT Team.
QUALIFICATIONS
- Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Data Science, Information Technology, or related field.
- Strong programming capability in Python.Experience with SQL, REST API integration, Git, Linux/Unix, debugging, testing, deployment, and production support.
- Basic understanding of AI/ML application lifecycle, model deployment, data pipeline support, and MLOps concepts.
- Familiarity with Docker, Kubernetes, CI/CD, or containerized deployment concepts.
- Preferred qualifications include experience with MLflow, KServe, Kubeflow, Kafka, RabbitMQ, OpenSearch, factory automation, equipment data, sensor data, or manufacturing systems.
- Fresh graduates may be considered only if they demonstrate strong software engineering capability, strong Python programming skills, and relevant academic, internship, or project experience in AI/ML, data engineering, software integration, factory automation, or related technical areas.
