Data Scientist - GenerativeAI

Job Title: Data Scientist / AI-ML Engineer (AI Agents & Machine Learning)

Experience: 2+ Years

Location: Bangalore

About the Role:

We are looking for a passionate and highly skilled AI/ML Developer / Data Scientist with proven experience in designing, building, and deploying intelligent systems using cutting-edge AI technologies. The ideal candidate will have hands-on expertise in Large Language Models (LLMs), Machine Learning, Deep Learning, Prompt Engineering, Vector Databases, and Agent Frameworks.

This role spans the entire AI/ML lifecycle from ideation and architecture to deployment and optimization with a strong emphasis on RAG pipelines, NLP, chatbot frameworks, and proof-of-concept (POC) development. Youll be working at the forefront of Generative AI, LLMs, Computer Vision, and Vector Database-powered RAG systems to create next-generation intelligent applications.

Key Responsibilities

Design, develop, fine-tune, and deploy end-to-end AI/ML solutions.

Work with both closed-source LLMs (OpenAI GPT, Claude, Gemini) and open-source models (BERT, LLaMA, Mistral, Gemma).

Architect and implement RAG pipelines using LangChain, LangGraph, CrewAI, and LlamaIndex.

Build and integrate AI agents, Agentic AI workflows, and chatbots for real-world applications.

Utilize Vector Databases (FAISS, Milvus, Qdrant, Weaviate, pgvector, ChromaDB) for semantic search and retrieval.

Apply prompt engineering and few-shot learning to optimize model outputs.

Develop computer vision solutions using YOLO and OpenCV for object detection, tracking, and video/image analytics.

Create scalable APIs and backends with FastAPI or Flask.

Perform EDA, data visualization, and ensure model explainability.

Deploy and manage AI/ML models on AWS, Azure, or GCP.

Rapidly deliver POCs and collaborate with cross-functional teams to validate solutions.

Maintain version-controlled, reproducible ML pipelines.

Must-Have Skills

Programming & Frameworks: Python, FastAPI

GenAI & LLMs: GPT, Claude, Gemini, BERT, LLaMA, Mistral, Gemma, HuggingFace Transformers

Frameworks: LangChain, LangGraph, CrewAI, LlamaIndex

Vector Databases: FAISS, Milvus, Qdrant, Weaviate, pgvector, ChromaDB

Computer Vision: OpenCV, YOLO object detection

NLP & RAG: Text classification, summarization, NER, prompt design, RAG pipelines

Model Lifecycle: Design, training, quantization, fine-tuning, deployment

Cloud: AWS, Azure, GCP

Databases: SQLite, PostgreSQL, MySQL, MongoDB (optional)

Visualization Tools: Matplotlib, Seaborn, Plotly, Streamlit

OS & Tools: Linux (CLI, scripting), Docker (optional), HuggingFace, chatbot platforms

Nice-to-Have

Contributions to open-source or GitHub projects

Experience with multi-modal LLMs

Strong background in statistics or academic research

Familiarity with startup-style POC pipelines and rapid experimentation

Educational Qualification:

B.Tech, M.Tech, MCA, BCA, or Bachelors/Masters degree in Computer Science, Data Science, AI/ML, or a related field.