Build modular, agent-driven AI systems using LangChain, LangGraph, and CrewAI
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate
Fine-tune LLMs using HuggingFace Transformers for tasks like document summarization, extraction, and classification
Design scalable and performant APIs using FastAPI (RESTful + async endpoints)
Perform EDA, feature engineering, and implement core ML algorithms
Collaborate with product and engineering teams to deliver production-grade solutions
Work on both real-time and batch AI systems, ensuring reliability and scalability

1–2 years of hands-on experience in AI/ML engineering or a related role
Working knowledge or experience with LangChain, LangGraph, or CrewAI
Proficiency in Python and FastAPI for backend development
Familiarity with vector databases (e.g., FAISS, Pinecone, Chroma) and RAG architectures
Experience with LLM fine-tuning using HuggingFace or similar frameworks
Good understanding of NLP tasks like NER, summarization, classification, and sentiment analysis
Solid foundation in EDA, supervised/unsupervised learning, and core ML algorithms
Comfortable working with APIs and integrating third-party services.

MNR Technologies Global Pvt Ltd

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