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 FastAPI/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 PyTorch
- 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 FastAPI / 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
- PyTorch, HuggingFace Transformers
- Vector DBs: Pinecone, FAISS, Chroma, Milvus
- FastAPI / 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.Tech / B.E / B.Sc / MCA or equivalent)
Soft Skills Required
- Strong analytical and problem-solving skills
- Ability to work independently and in a team environment
- Strong communication and documentation skills
- Ability to handle multiple tasks and deliver within deadlines
