AI Engineer

6 days ago

Bangkok, Bangkok, Thailand Nodesnow Labs Co.,Ltd. Full time

Responsibilities

  • Design, develop, and deploy AI, LLM, and machine learning solutions to support business applications such as customer behavior prediction, collaboration intelligence, document processing, and workflow automation.
  • Build and maintain pipelines for data ingestion, embedding generation, RAG (Retrieval-Augmented Generation), and model serving.
  • Collaborate closely with cross-functional teams (Data Engineering, Product Design, IT, Business Units, and external Vendors) to identify AI-driven opportunities and deliver practical, scalable solutions.
  • Develop and optimize algorithms across LLMs, AI Voice/Speech models, OCR, and predictive analytics to support various internal and external business use cases.
  • Conduct data exploration, feature engineering, model evaluation, and performance tuning to ensure reliability and robustness.
  • Implement best practices in MLOps, including model versioning, monitoring, retraining, and CI/CD pipelines on Azure.
  • Research emerging AI/ML technologies (OpenAI, Azure AI, LangChain, vector databases, multimodal models, etc.) and evaluate their applicability to enhance the company's products.
  • Document architectures, workflows, and model behaviors clearly, and communicate insights effectively to both technical and non-technical stakeholders.

Requirements

  • Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Engineering, Mathematics, or a related field.
  • 2–5 years of hands-on experience building and deploying AI/ML or LLM-based systems in production.
  • Proficiency in Python and , with experience in LLM tooling (e.g., LangChain, LlamaIndex, Transformers).
  • Experience with Azure cloud services (Azure AI, Azure Functions, App Service, Storage, Communication Services) and MLOps practices.
  • Strong understanding of data structures, algorithms, APIs, vector databases, and general software engineering principles.
  • Familiarity with embeddings, prompt engineering, chunking strategies, RAG pipelines, and model evaluation metrics.
  • Excellent problem-solving, analytical thinking, and communication skills.

  • Bonus:

  • Experience integrating external automation tools.

  • Experience with real-time collaboration systems, knowledge management, or enterprise workflow tools.

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