3.0 - 8.0 years

9 - 19 Lacs

Coimbatore

Hybrid

: Generative AI Engineer : 3 to 5 years : We are looking for a Generative AI Engineer with 3 to 5 years of hands-on experience in Retrieval-Augmented Generation (RAG), Agentic AI, and Data Pipelines. The ideal candidate will have real-time experience in developing and deploying AI-powered solutions, working with advanced language models, and optimizing AI workflows for production environments. : 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. & : 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. 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) and LLM fine tuning. Familiarity with privacy-preserving AI techniques and responsible AI frameworks. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation. ____________________________________________________________________________ "Python/Gen AI Developer" Experience: 5 to 8 Location: Coimbatore/Remote Notice Period: Immediate Joiners are Preferred : 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. Role & responsibilities Preferred candidate profile

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