Lead Data Scientist

7 days ago

Bengaluru, Karnataka, India Weekday AI Full time ₹ 10,00,000 - ₹ 50,00,000 per year

This role is for one of the Weekday's clients

Salary range: Rs Rs 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

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