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Machine Learning Engineer


We are looking for a talented Machine Learning Engineer to join our team and play a key role in the R&D of innovative AI/ML products for the Insurance and Microfinance industries.

Key Responsibilities:

  • Develop and implement machine learning models using state-of-the-art techniques
  • Work on NLP projects, including transformer-based models
  • Train and evaluate Large Language Models (LLMs) and Small Language Models (SLMs)
  • Implement computer vision solutions using Google Vision AI
  • Develop Intelligent Document Processing systems, including OCR
  • Manage data annotation processes, including automated annotation
  • Perform web crawling for data collection
  • Fine-tune custom models for specific use cases


  • A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent experience)
  • Proficiency in Python programming
  • Strong understanding of Transformer algorithms and NLP techniques
  • Experience with Python libraries for Transformers 
  • Familiarity with transformer-based embedding models (e.g., E5, SBERT)
  • Ability to train and evaluate sLLM models like Llama and Mistral
  • Experience with Google Vision AI and Google APIs
  • Knowledge of OCR and Intelligent Document Processing
  • Familiarity with annotation tools like LabelMe
  • Web crawling experience
  • Excellent communication and collaboration skills
  • A passion for innovation and applying AI/ML to solve real-world challenges
  • Experience working in the Insurance or Microfinance industries is a plus
  • Experience with cloud platforms (e.g., AWS, GCP) is a plus
  • Thai or Korean language skill is a plus


  • Competitive salaries based on experience.

  • Transportation and communication Allowances

  • Quarterly best performer award 

  • A positive and inclusive work environment

  • Exciting opportunities for professional growth and development

How to apply

  • If you think you are good enough for this role, you can apply with your resume to careers@blue-stone.net.

  • For more inquiries, please contact 09251188433 during working hours.