About the Role We are looking for highly skilled and motivated Data Scientists / NLP Data Scientists / ML Engineers with strong hands-on experience in Machine Learning, Natural Language Processing (NLP), and Large Language Models (LLMs).
The ideal candidate should have practical exposure to building and deploying ML/NLP solutions in production environments, especially involving LLM fine-tuning, RAG pipelines, embeddings, and vector databases.
Key Responsibilities Design, build, train, and optimize Machine Learning and NLP models Work on LLM fine-tuning, inference, evaluation, and prompt engineering Develop and implement RAG (Retrieval-Augmented Generation) pipelines Build pipelines using embeddings and vector databases (Pinecone, FAISS, Chroma, Milvus, etc.) Perform data preprocessing, feature engineering, and dataset preparation Optimize models for latency, scalability, and performance Deploy ML/NLP models using Fast API/Flask and integrate with production systems Collaborate with engineering, product, and business teams to understand requirements and deliver solutions Monitor model performance and ensure continuous improvement through experimentation Mandatory Technical Skills Strong proficiency in Python Strong fundamentals in Machine Learning & Deep Learning Strong knowledge of NLP techniques Experience with Large Language Models (LLMs) Hands-on experience with Py Torch Hands-on experience with Hugging Face Transformers Experience with Vector Databases (Pinecone, FAISS, Chroma, Milvus, etc.) Data preprocessing, model training, evaluation, and optimization experience Preferred / Good-to-Have Skills Model deployment experience using Fast API / Flask Knowledge of Docker and containerized deployment Version control using Git Familiarity with Jupyter Notebook / VS Code Exposure to Cloud platforms (AWS / Azure / GCP – optional) Understanding of MLOps concepts and CI/CD pipelines (added advantage) Tools & Technologies Python, SQL Py Torch, Hugging Face Transformers Vector DBs: Pinecone, FAISS, Chroma, Milvus Fast API / Flask Docker, Git Jupyter Notebook / VS Code Cloud (optional) Project / Domain Exposure Required Strong experience in NLP-based projects Exposure to LLM training, fine-tuning, inference, evaluation, and optimization Experience in developing end-to-end ML/NLP pipelines Deployment experience in real-time production environments is preferred Educational Qualification Bachelor’s Degree (B.
