AI Engineer

AI Engineer focus on designing, building, and deploying AI systems into production. This role will bridge the gap between data science experimentation and scalable, maintainable and real-world applications. 

Main role and responsibilities:

• Model Deployment Convert ML models from prototypes into production systems (e.g., via APIs, pipelines, or microservices).
• System Integration Integrate AI models into existing applications or workflows (e.g., credit scoring, chatbots, fraud detection).
• Optimization Ensure performance efficiency, scalability, and reliability of AI systems.
• AI Infrastructure & Tools Work with GPU clusters, cloud platforms (AWS, Azure, GCP), or tools like Databricks, MLflow, Docker, and Kubernetes.
• MLOps & Automation Implement continuous integration and continuous delivery (CI/CD) for AI models and monitor model drift.
• Collaboration Work closely with Data Engineers and Data Scientists to operationalize models and automate pipelines.

Qualification:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Able to communicate both writing and speaking in English and Thai
• Minimum of 3 years of experience in data engineering, with a focus on financial services or consulting.
• Proven track record of designing and implementing complex data solutions, including data lakes, data warehouses, and real-time streaming platforms.
• Hands-on experience with cloud-based technologies, such as AWS, Azure, or GCP, and proficiency in SQL, Python, Scala, or Java.
• Strong understanding of AI and machine learning concepts, with experience in deploying models in production environments.
• Excellent communication skills and ability to effectively collaborate with cross-functional teams.
• Demonstrated leadership capabilities, including the ability to lead technical projects, mentor junior team members, and drive innovation.

Common Technical Stack:

• Languages: Python, Java, Go, or C++
• Frameworks: TensorFlow, PyTorch, Hugging Face
• Tools: MLflow, Airflow, Kubeflow, Docker, Kubernetes, FastAPI
• Cloud: AWS Sagemaker, Azure ML, VertexAI
• Others: Git, APIs, REST, CI/CD pipelines

Please note that once we received the CV, we will start the screening and selection process. If your application proceeds to the next step, you will receive an update from us within one week. We look forward to receiving your application!