Key responsibilities
- Design, develop, and deploy AI/ML solutions that address business problems and create measurable business value.
- Build and maintain AI pipelines for data preparation, model training, deployment, monitoring, and continuous improvement.
- Integrate AI capabilities into enterprise applications, products, and business processes through APIs and cloud platforms.
- Collaborate with business, product, data, and engineering teams to translate business requirements into scalable AI solutions.
- Monitor and optimize AI models to ensure accuracy, reliability, scalability, and operational performance throughout the model lifecycle.
- Implement responsible AI practices by ensuring model governance, security, explainability, privacy, and regulatory compliance.
- Evaluate emerging AI technologies and tools to accelerate innovation and improve engineering productivity.
- Promote AI engineering best practices across model development, MLOps, testing, deployment, and lifecycle management.
- Performs other related tasks which may be assigned from time to time.
Qualifications, Experience and Skillsets
- AI engineering experience: Hands-on experience developing and deploying machine learning, generative AI, or data-driven software solutions.
- AI and machine learning expertise: Strong knowledge of machine learning, large language models, prompt engineering, model evaluation, natural language processing, and conversational AI.
- Technical expertise: Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn, with knowledge of data structures, algorithms, and software engineering principles.
- Generative AI technologies: Experience with enterprise AI platforms such as Azure OpenAI, OpenAI, AWS, or GCP, including embeddings, vector databases, retrieval-augmented generation, and LLMOps tools.
- AI platform and data skills: Experience building reusable AI platforms, data pipelines, feature engineering processes, model services, and integration components that support multiple use cases.
- Application integration: Experience building APIs, microservices, serverless functions, containers, and cloud-based AI applications.
- MLOps and deployment: Experience with CI/CD, model deployment, versioning, monitoring, testing, and ongoing model improvement.
- Responsible AI and governance: Understanding of AI security, privacy, ethics, explainability, model risk, governance, and regulatory requirements.
- Required certificates: AWS Certified Machine Learning Engineer - Associate, Certification Certified AI Expert Global Tech Council, Performance Tuning and Optimizing SQL Database, Certified Data Management Professionals (CDMP)
Talent Acquisition Team, Human Resources Management Department (Head Office)
Muang Thai Life Assurance Public Company Limited
250 Ratchadaphisek Rd., Huaykwang, Bangkok 10310
Website: www.muangthai.co.th
Line Official Account: @mtlcareer
LinkedIn: Muang Thai Life Assurance Public Company Limited
Remark: This position requires a criminal record information check prior consideration for employment to ensure safety and maintain standards of the organization.
