Chief AI Architect

1 day ago

Erode, Tamil Nadu, India beBeeSenior Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

AI Engineering Opportunity

We are seeking an experienced Senior AI Engineer to drive the development and optimization of cutting-edge AI applications. This role requires expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques.

  • Design and Optimize AI Solutions: Develop, fine-tune, and integrate LLMs with RAG architectures to enhance AI solution efficiency and accuracy.
  • Model Development and Deployment: Implement and fine-tune models to improve response relevance and contextual accuracy using frameworks like Hugging Face Transformers or OpenAI API.
  • Pipeline Development: Create data retrieval, indexing, and augmentation pipelines to improve knowledge grounding and vector database integration.
  • Vector Database Integration: Work with vector databases (e.g., Pinecone, FAISS, Weaviate) to enhance retrieval capabilities and optimize model inference for performance and scalability.
  • Enterprise Application Integration: Seamlessly integrate AI models with enterprise applications and APIs, ensuring interaction and data exchange.
  • Ethical AI Implementation: Address bias, explainability, and data security concerns to ensure responsible AI implementation.
  • Technological Advancements: Stay updated with the latest advancements in generative AI, deep learning, and RAG techniques to continuously improve AI engineering practices.

Requirements:

  • 8+ Years Experience in Software Development: Strong background in software development according to industry standards, with a focus on developing scalable and maintainable code.
  • LLM Training and Deployment Expertise: Hands-on experience training and deploying LLMs using popular frameworks like Hugging Face Transformers, OpenAI API, or LangChain.
  • RAG Techniques and Vector Search Proficiency: Solid understanding of Retrieval-Augmented Generation (RAG) techniques and vector search methodologies, including proficiency in vector databases like FAISS, Pinecone, ChromaDB, or Weaviate.
  • NLP, Deep Learning, and Transformer Architecture Knowledge: Comprehensive understanding of NLP, deep learning, and transformer architectures, as well as proficiency in Python and ML libraries (TensorFlow, PyTorch, LangChain, etc.).
  • Cloud Platform and MLOps Experience: Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps workflows, including containerization (Docker, Kubernetes) for scalable AI deployments.
  • Problem-Solving and Communication Skills: Excellent problem-solving and debugging skills, combined with strong communication and teamwork abilities.
  • Education Background: Bachelor's or Master's degree in computer science, AI, Machine Learning, or a related field.

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