Data Scientist with Gen AI

Role Overview

We are looking for an experienced Data Scientist Generative AI with strong expertise in Data Science, Machine Learning, Deep Learning, NLP, and Generative AI. The candidate will be responsible for designing, developing, and deploying AI/ML solutions and LLM-powered applications using modern GenAI technologies.

The ideal candidate should have hands-on experience with Python, SQL, Machine Learning, LLMs, RAG, Prompt Engineering, Vector Databases, NLP, and AI/Agentic frameworks.

Key Responsibilities

• Design, develop, and deploy end-to-end Machine Learning and Generative AI solutions.
• Perform Exploratory Data Analysis (EDA), data preprocessing, feature engineering, statistical analysis, and model development.
• Build and optimize ML/DL models for predictive and prescriptive analytics.
• Develop LLM-powered applications using OpenAI, Azure OpenAI, Gemini, Llama, Mistral, Claude, or similar models.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines.
• Work with embeddings, semantic search, document chunking, reranking, and retrieval optimization.
• Develop applications using frameworks such as LangChain, LlamaIndex, LangGraph, or similar frameworks.
• Work on Agentic AI / AI Agents and multi-step AI workflows.
• Implement prompt engineering techniques to improve accuracy, relevance, and reliability of LLM responses.
• Work with Vector Databases such as FAISS, Pinecone, ChromaDB, Weaviate, or equivalent.
• Fine-tune and optimize LLMs where required using techniques such as LoRA, QLoRA, or PEFT.
• Develop NLP solutions including text classification, summarization, semantic search, question answering, information extraction, and chatbot applications.
• Build APIs and integrate AI/ML solutions with enterprise applications using FastAPI/Flask and REST APIs.
• Evaluate GenAI applications for accuracy, relevance, hallucination, latency, cost, and overall performance.
• Deploy and monitor AI/ML applications in cloud and production environments.
• Collaborate with Data Engineering, Software Engineering, Product, and Business teams.
• Maintain documentation, reusable AI components, prompt libraries, and ML/GenAI pipelines.

Mandatory Skills

• Strong hands-on experience with Python.
• Strong knowledge of SQL.
• Strong fundamentals in Statistics, Probability, Machine Learning, and Data Science.
• Experience with Pandas, NumPy, Scikit-learn.
• Experience with PyTorch or TensorFlow.
• Hands-on experience with Generative AI and LLMs.
• Strong understanding of RAG architecture.
• Hands-on experience with Prompt Engineering.
• Experience with Embeddings and Vector Databases.
• Experience with LangChain / LlamaIndex / LangGraph or equivalent.
• Knowledge of NLP and Transformer architectures.
• Experience integrating LLMs through APIs such as OpenAI, Azure OpenAI, Gemini, AWS Bedrock, or equivalent.
• Knowledge of REST APIs and FastAPI/Flask.
• Good understanding of model evaluation and optimization.

Good to Have

• Experience with Agentic AI / Multi-Agent Systems.
• Experience with LoRA, QLoRA, PEFT, or LLM fine-tuning.
• Experience with AWS, Azure, or GCP.
• Knowledge of Databricks, Spark, MLflow, Kubeflow, or Azure ML.
• Experience with Docker and CI/CD.
• Knowledge of MLOps / LLMOps.
• Experience with multimodal AI.
• Experience with Power BI, Tableau, or other data visualization tools.
• Experience handling large-scale structured and unstructured datasets.