3.0 - 8.0 years

5 - 15 Lacs

Coimbatore

Work from Office

: * Design, develop, and fine-tune Large Language Models (LLMs) for various in-house applications. * Implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. * Develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. * Build and manage data pipelines for processing, transforming, and feeding structured/unstructured data into AI models. * Ensure scalability, performance, and security of AI-driven solutions in production environments. * Collaborate with cross-functional teams, including data engineers, software developers, and product managers. * Conduct experiments and evaluations to improve AI system accuracy and efficiency. * Stay updated with the latest advancements in AI/ML research, open-source models, and industry best practices. & : * Strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. * Hands-on experience with RAG architectures, including vector databases (e.g., Pinecone, ChromaDB, Weaviate, OpenSearch, FAISS). * Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks. * Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. * Experience in Python web frameworks such as FastAPI, Django, or Flask. * Experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. * Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes). * Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications. * Strong understanding of vector search, embedding models, and hybrid retrieval techniques. * Experience with optimizing inference and serving AI models in real-time production systems. -- : * Experience with multi-modal AI (text, image, audio). * Familiarity with privacy-preserving AI techniques and responsible AI frameworks. * Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation.

Posted 2 weeks ago

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