Experience: 6–12 Years

Key Responsibilities

Design, develop, and deploy machine learning and GenAI solutions in production environments

Build and optimize Retrieval-Augmented Generation (RAG) pipelines

Design, develop, and orchestrate AI agents using modern Agentic AI frameworks to automate complex business workflows.

Develop multi-agent systems with planning, reasoning, tool usage, and workflow orchestration capabilities.

Fine-tune and evaluate Large Language Models (LLMs)

Develop prompt engineering strategies and evaluation frameworks

Implement scalable ML pipelines using Python

Work with structured and unstructured data sources

Collaborate with Engineering, Product, and SMEs to deliver AI-driven features

Monitor model performance, drift, and reliability in production

Conduct experimentation, A/B testing, and performance benchmarking

Contribute to architecture design for AI-powered systems

Required Technical Skills

Core Stack

Python (advanced proficiency)

Machine Learning (supervised/unsupervised learning, NLP)

Generative AI (LLMs, prompt engineering, embeddings)

RAG architecture and vector search

Agentic AI concepts including planning, memory, tool calling,



workflow orchestration, and multi-agent collaboration

Model evaluation and validation frameworks

ML & AI Tools

Experience with Agentic AI frameworks such as CrewAI, AutoGen, Semantic Kernel, or similar

Experience building AI agents with tool integration, function calling, and workflow orchestration

Understanding of agent memory, state management, routing, and human-in-the-loop workflows

LangChain / LlamaIndex (or similar frameworks)

Scikit-learn / XGBoost / LightGBM

PyTorch / TensorFlow

HuggingFace / OpenAI / LLM APIs

Vector databases (Pinecone, FAISS, Weaviate, OpenSearch, etc.)

Data & Infrastructure

SQL and data querying

Experience with AWS / Azure / GCP

CI/CD for ML deployments

Model tracking tools (MLflow preferred)

REST APIs/FastAPI for AI service deployment

Valuable to Have

Experience in legal, regulatory, or publishing domains

Experience with model monitoring and MLOps

Knowledge of fine-tuning techniques (LoRA, PEFT, QLoRA)

Experience with multi-agent frameworks (AutoGen, LangGraph, etc.)

📌 Senior Data Scientist (Gurugram)
🏢 Neurealm
📍 Gurugram