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AI Solution Engineer (Data Scientist Generative AI)

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Onsite

AI Solution Engineer (Data Scientist Generative AI)

Mitr Phol Sugar Corp., Ltd.

AI Solution Engineer (Data Scientist Generative AI)

Skills

Google Cloud PlatformPythonKnowledge ManagementMachine LearningAIAWSNLP / Natural Language ProcessingSupply ChainComplianceAzure

22 days ago

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Important information


Contract type:

Freelance / Contract

Location:

Bangkok, Thailand

Work mode:

Onsite

Published on:

30 September 2026

What they need


ชื่อตำแหน่ง : AI Solution Engineer -Data Scientist – Generative AI ( Mitr Phol AI)

รูปแบบการจ้าง : Fix Term Contract 2 ปี

To design, build, and optimize Large Language Models (LLMs) and Generative AI solutions that enhance enterprise knowledge management, automation, and decision support across all business units.

Responsibility

  • LLM Development: Build and fine-tune LLMs for enterprise-specific tasks (knowledge retrieval, summarization, copilots, chatbots).
  • Prompt Engineering: Design and test effective prompts for high-quality, reliable outputs.
  • RAG Pipelines: Implement Retrieval-Augmented Generation pipelines for context-aware AI systems.
  • Integration: Embed GenAI solutions into enterprise workflows (HR, Finance, Factory, Supply Chain).
  • Evaluation: Benchmark LLM performance for accuracy, faithfulness, bias, hallucination, and cost efficiency.
  • Collaboration: Work closely with AI Product Managers, Business Analysts, and Data Engineers to deliver scalable GenAI solutions.
  • Governance: Ensure responsible use of GenAI by embedding bias detection, fairness checks, explainability, and compliance with AI ethics.

Requirement

  • Bachelor, master’s degree in Artificial Intelligence, NLP, Machine Learning, or related.
  • 2–7 years of experience in applied AI, with at least 2 years in LLM/GenAI projects.
  • Proficiency in Python, Hugging Face Transformers, LangChain, LlamaIndex.
  • Strong background in NLP, embeddings, RAG, and fine-tuning LLMs.
  • Experience with cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI).
  • Familiarity with vector databases (FAISS, Pinecone, Weaviate, Qdrant).
  • Knowledge of evaluation frameworks for LLMs (e.g., RAGAS, TruLens).
  • Familiarity with MLOps for LLMs (LLMOps).

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