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 contemporary 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