Roles & Responsibilities:

- Design and develop intelligent AI-based applications using advanced NLP and LLM techniques to solve real-world business challenges in financial services.
- Build and optimize Retrieval-Augmented Generation (RAG) pipelines leveraging structured and unstructured financial data.
- Integrate and orchestrate LLMs/SLMs for question-answering, summarization, semantic search, and document understanding.
- Develop and maintain RESTful APIs (sync and async) to serve NLP models and chatbot interfaces using frameworks like FastAPI, Flask, etc.
- Implement semantic search, hybrid search, and text retrieval systems using Elasticsearch and vector databases (e.g., FAISS, Pinecone, Weaviate).
- Perform NLP tasks such as entity recognition, text classification, intent detection, embedding generation, and sentiment analysis.
- Monitor and fine-tune LLM/SLM performance with real-world user data to improve relevance, latency, and accuracy.
- Build, train, and evaluate deep learning models for NLP tasks including classification, NER, summarization, and embedding generation.
- Develop traditional machine learning models (e.g., regression, decision trees, clustering)



for structured data analysis and prediction tasks.

Tech Stack & Requirements:

- 3 years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.
- Solid hands-on experience in Python programming, backend development, and API development.
- Experience with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.
- Hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, or knowledge-based AI applications.
- Experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, or Azure OpenAI.
- Experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI or Flask.
- B.Tech / M.Tech from Tier 1 Colleges (IIT, NIT, BITS, IIIT, DTU, NSUT) is mandatory.
- Candidate should be below 28 years of age.

Interview Process:

- 3 Technical Rounds
- Underwriting Call
- Criminal Check
- HR Discussion

📌 Data Scientist/AI Engineer - Generative AI (India)
🏢 The Job Sphere
📍 India