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AI Document Intelligence Specialist

2 weeks ago

Coimbatore, Tamil Nadu, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Document Intelligence Engineer

We're seeking a skilled Document Intelligence Engineer to develop and implement AI-driven solutions for intelligent document processing. This is an exciting opportunity to leverage your expertise in large language models, vision-language models, and deep learning techniques to drive business growth.

Key Responsibilities:
  • Fine-tune and optimize open-source and commercial LLMs/VLMs for structured and unstructured document processing tasks, including OCR extraction, entity recognition, key-value pairing, summarization, and layout understanding.
  • Apply advanced PEFT techniques, such as LoRA and QLoRA, to enable efficient deployment and experimentation.
  • Design LLM-based document intelligence pipelines for various use cases.
  • Develop and manage prompting techniques tailored to document use-cases.
  • Implement LangChain-based workflows integrating tools, agents, and vector stores for RAG-style processing.
  • Monitor experiments and production models using ML observability tools.
  • Work with leading LLM/VLM APIs for hybrid system design.
  • Collaborate with cross-functional teams to deliver scalable, production-ready ML systems and continuously improve model performance.
Required Skills & Experience:
  • Hands-on experience with transformer architectures and libraries like HuggingFace Transformers.
  • Deep knowledge of fine-tuning strategies for large models, including LoRA, QLoRA, and other PEFT approaches.
  • Experience in prompt engineering and developing advanced prompting strategies.
  • Familiarity with LangChain, vector databases, and tool/agent orchestration.
  • Strong applied knowledge of leading LLM/VLM APIs.
  • Proficiency in model training, tracking, and monitoring using ML tools.
  • Solid understanding of deep learning, machine learning, natural language processing, and computer vision concepts.
  • Experience working with document AI models and OCR tools.
  • Proficient in Python, PyTorch, and related ML tooling.
Nice-to-Have:
  • Experience with multi-modal architectures for document + image/text processing.
  • Knowledge of RAG systems, embedding models, and custom vector store integrations.
  • Experience in deploying ML models via frameworks like FastAPI or Triton.
  • Contributions to open-source AI tools or model repositories.
  • Exposure to MLOps, CI/CD pipelines, and data versioning.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.