Senior Data Scientist

Neurealm; Gurugram District; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Neurealm is seeking an experienced AI/ML engineer to design, develop, and deploy cutting-edge GenAI and ML solutions in production. You will build Retrieval-Augmented Generation (RAG) pipelines and orchestrate AI agents to automate complex business workflows.

The role involves fine-tuning LLMs, developing prompt strategies, and evaluating model performance across production systems. Collaboration with Engineering, Product, and SMEs will drive AI-powered features and scalable ML pipelines.

Qualifications

• Experience building ML pipelines in production environments.
• Proficient in cloud platforms (AWS/Azure/GCP).
• Familiarity with agent-based frameworks and tool integration.

Responsibilities

• Design, develop, and deploy ML/GenAI solutions in production.
• Build RAG pipelines and vector search.
• Develop AI agents and multi-agent workflows for business automation.
• Tune and evaluate LLMs; implement prompt strategies.
• Monitor model performance and reliability in production.
• Collaborate with Eng/PM/SMEs to deliver AI features.

Skills

Python programming

Machine Learning

NLP

Generative AI

RAG architecture

Agentic AI

Model evaluation

Tools

CrewAI

AutoGen

Semantic Kernel

LangChain

LlamaIndex

Scikit-learn

XGBoost

LightGBM

PyTorch

TensorFlow

Job description

• 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

Data & Infrastructure

• SQL and data querying
• Experience with AWS / Azure / GCP
• CI/CD for ML deployments
• Model tracking tools (MLflow preferred)

Good 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.)