About the job :

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 : ~2 Years

Qualifications :

- Bachelor's or Masters 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, LLaMA).

- 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 PyTorch or TensorFlow.

- 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 LangChain, CrewAI, or LangGraph.

- Experience building REST APIs or Flask/FastAPI 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, LoRA)