Lead Data Scientist

This role is for one of the Weekday's clients

Salary range: Rs 1200000 - Rs 3400000 (ie INR 12-34 LPA)

Min Experience: 5 years

Location: Bangalore

JobType: full-time

We are seeking an experienced Lead Data Scientist with deep expertise in large language models (LLMs), advanced AI system architecture, and real-time data processing. The ideal candidate will possess strong technical leadership and hands-on development skills, driving end-to-end AI/ML solutions from experimentation to production deployment.

Requirements

Key Responsibilities

• Design, develop, and optimize advanced machine learning and AI architectures leveraging cutting-edge LLM technologies.
• Build robust, scalable systems using Python and distributed data processing frameworks such as Apache Spark.
• Architect efficient solutions for Agentic AI systems, including multi-agent orchestration, inter-agent memory sharing, and workflow automation.
• Lead event-driven and real-time analytics solutions that support high-performance applications.
• Operationalize AI pipelines using Azure DevOps and LLMOps tools for deployment, monitoring, and lifecycle management.
• Work extensively with Azure OpenAI, vector databases, and RAG frameworks, including API integration, fine-tuning, and prompt engineering.
• Utilize cloud infrastructure (Azure/AWS/GCP) and containerization platforms like Kubernetes and Docker for scalable model deployment.
• Apply comprehensive knowledge of data lakes, data governance, and storage optimization strategies.
• Build applications using LangChain, LlamaIndex, Semantic Kernel, and other modern LLM frameworks.
• Provide mentorship, thought leadership, and technical guidance to the AI and data teams.

Required Skills & Experience

• Large Language Models (OpenAI GPT-4o, O1, Claude, Gemini, Llama, Phi, etc.)
• Agentic AI & RAG Architecture
• Python, FastAPI, Apache Spark
• Azure OpenAI / AWS / GCP AI Services
• Vector Databases & Model Fine-Tuning
• LangChain, LlamaIndex, Semantic Kernel
• Kubernetes, Docker, and container orchestration
• Real-time streaming & event-driven systems
• LLMOps & Azure DevOps
• Strong leadership, problem-solving, and analytical skills