Senior/Lead Data Scientist - GEN AI

AI overview

Develop a generative AI chatbot platform integrating multiple systems to deliver secure responses, owning architecture and hands-on development from design to deployment.

About Us

We turn customer challenges into growth opportunities. Material is a global strategy partner to the world’s most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences. We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve. Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners.

Role -  Senior / Lead Data Scientist – Generative AI (RAG & Multi-Agent Systems)

Experience

6+ years (Senior / Lead Data Scientist)

Role Summary

We are looking for a Senior Developer/Lead Data Scientist to build and scale an enterprise-grade GenAI chatbot platform that integrates with multiple RAG (Retrieval Augmented Generation) systems to deliver accurate, grounded, and secure responses at high concurrency. You will own architecture and hands-on development across LLM orchestration, retrieval pipelines, evaluation, and production deployment.

Key Responsibilities

  • Design and build a scalable GenAI chatbot that orchestrates and calls multiple RAG systems (routing, retrieval, re-ranking, response generation).
  • Implement multi-agent architectures (where required) using frameworks like LangChain, AutoGen, or similar.
  • Develop robust Python services/APIs (FastAPI preferred) with streaming responses, retries, rate limits, and observability.
  • Build and optimize RAG pipelines: data ingestion, chunking strategies, embeddings, vector indexing, hybrid retrieval, metadata filtering, and context management.
  • Evaluate and improve response quality using offline/online evaluation, feedback loops, and guardrails to reduce hallucinations.
  • Integrate Azure OpenAI / OpenAI GPT models and manage prompt/versioning strategies for different use-cases.
  • Ensure production readiness: performance optimization, cost control, caching, monitoring, alerting, CI/CD, and secure deployments.
  • Collaborate with product and engineering teams to define requirements, SLAs, and rollout plans.

Must Have Skills

  • Strong proficiency in Python and AI/ML libraries: PyTorch / TensorFlow, Scikit-learn.
  • Hands-on experience with Generative AI and LLMs (e.g., Azure OpenAI GPT) in production.
  • Strong understanding of Data Science fundamentals: preprocessing, feature engineering, model evaluation, metrics.
  • Experience building RAG systems: embeddings, vector search, retrieval strategies, re-ranking, and grounding.
  • Experience with LangChain, AutoGen, or similar orchestration frameworks.
  • Solid software engineering practices: clean architecture, testing, code review, documentation.

Nice to Have

  • Familiarity with Big Data tools: Spark, Hadoop, Databricks.
  • Experience with databases: SQL / NoSQL, and vector databases/search (Azure AI Search, Pinecone, Weaviate, Qdrant, etc.).
  • Experience with ReactJS for building responsive chat UIs with streaming.
  • Knowledge of MLOps tooling and cloud deployment patterns (Docker/Kubernetes).

What You’ll Build / Deliverables

  • Multi-RAG chatbot orchestration layer (routing + tool calling).
  • Scalable retrieval and generation services with caching and observability.
  • Evaluation harness (quality + hallucination checks) and feedback-driven improvements.
  • Secure, multi-tenant ready system (if applicable) with access control.

Education

  • B.Tech/M.Tech in CS/IT/Data Science (or equivalent practical experience).

    Who We Are & What We Care About

    ·       Material is a global company and we work with best-of-class brands worldwide. We also create and launch new brands and products, putting innovation and value creation at the center of our practice. Our clients are in the top of their class, across industry sectors from technology to retail, transportation, finance and healthcare.

    ·       Material employees join a peer group of exceptionally talented colleagues across the company, the country, and even the world. We develop capabilities, craft and leading-edge market offerings across seven global practices including strategy and insights, design, data & analytics, technology and tracking. Our engagement management team makes it all hum for clients.

    ·       We prize inclusion and interconnectedness. We amplify our impact through the people, perspectives, and expertise we engage in our work. Our commitment to deep human understanding combined with a science & systems approach uniquely equips us to bring a rich frame of reference to our work.

    ·       A community focused on learning and making an impact. Material is an outcomes focused company. We create experiences that matter, create new value and make a difference in people's lives.

     

    What We Offer

    ·       Professional Development and Mentorship.

    ·       Hybrid work mode with remote friendly workplace. (6 times in a row Great Place To Work Certified).

    ·       Health and Family Insurance.

    ·       40+ Leaves per year along with maternity & paternity leaves.

    ·       Wellness, meditation and Counselling sessions.

 

Perks & Benefits Extracted with AI

  • Health Insurance: Health and Family Insurance.
  • Professional Development and Mentorship: Professional Development and Mentorship.
  • Paid Time Off: 40+ Leaves per year along with maternity & paternity leaves.
  • Remote-Friendly: Hybrid work mode with remote friendly workplace.
  • Wellness Stipend: Wellness, meditation and Counselling sessions.
Ace your job interview

Understand the required skills and qualifications, anticipate the questions you may be asked, and study well-prepared answers using our sample responses.

Lead Data Scientist Q&A's
Report this job
Apply for this job