Llm/nlp engineer

3 weeks ago


Delhi, India Innefu Labs Full time

About the Company Founded in 2010, Innefu is an AI-driven R&D company focused on cutting-edge Data Analytics and Information Security solutions. With over 100 installations across the Indian Subcontinent, Middle East, and Southeast Asia, we provide AI-powered solutions to defense, law enforcement, financial institutions, and Fortune 500 companies. Our mission is to solve real-world security and data challenges through innovation and deep technical research. About the Role We are looking for a passionate and curious LLM/NLP Engineer with ~1.5 years of hands-on experience in working with transformer-based models and natural language processing. You will work under the guidance of senior engineers and contribute to the development, fine-tuning, and deployment of LLM-powered applications. This is an excellent opportunity for someone early in their AI career who wants to work on real-world, large-scale NLP challenges involving retrieval systems, agentic workflows, and open-source LLMs. On-site – NSP, Delhi Job Type: Full-time (WFO) Experience Required: ~1.5 Years Qualifications Bachelor's or Master’s degree in Computer Science, Machine Learning, AI, or a related field. Candidates with relevant project experience or certifications in NLP/ML will also be considered. Responsibilities Assist in fine-tuning and deploying LLMs using transformer-based architectures (e.g., BERT, GPT, LLa MA). Contribute to the development of simple autonomous agents or chatbots using open-source tools. Support integration of vector databases (like FAISS or Milvus) for semantic search and memory storage. Work on LLM inference and basic optimization under guidance (e.g., batch inference, prompt tuning). Collaborate with the team on RAG pipelines and learn to integrate retrieval mechanisms into LLM workflows. Stay up to date with basic advancements in LLMs and NLP tools. Required Skills ~1.5 years of experience in NLP or machine learning projects (academic, research, or industry). Hands-on experience with transformer models using Hugging Face Transformers or similar libraries. Basic understanding of LLMs and fine-tuning techniques. Proficiency in Python, with experience using Py Torch or Tensor Flow. Familiarity with vector databases (e.g., FAISS, Milvus) and basic semantic search. Good problem-solving skills and eagerness to learn advanced AI systems. Preferred Skills Exposure to agentic AI frameworks like Lang Chain, Crew AI, or Lang Graph. Experience building REST APIs or Flask/Fast API services to serve NLP models. Familiarity with RAG (Retrieval-Augmented Generation) pipelines. Contributions to open-source NLP/ML projects or Kaggle competitions. Understanding of basic model optimization (e.g., quantization, distillation, Lo RA).


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