Live opening · Posted 1 day ago

Data Scientist Senior/Lead

Celebal Technologies · India (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyCelebal Technologies
LocationIndia (Remote)
Work modeNo
SourceLinkedin
Listed1 day ago

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About the role

Description supplied by the original job listing.

Senior Data Scientist – GenAI & Agentic AI
Location: Jaipur / Bengaluru / Pune / Hyderabad / Noida / Ahmedabad/ Gurugram / Chennai (Hybrid/Onsite)
Experience: 5–9 Years
Department: Data Science & AI Practice
About Celebal Technologies
Celebal Technologies is a premier digital transformation and cloud-native solutions enterprise, recognized as a global Microsoft and Databricks partner. We bridge enterprise challenges with modern intelligence across Big Data, Cloud Infrastructure, Data Engineering, and Applied Artificial Intelligence.
Role Overview
We are seeking an experienced Senior Data Scientist with end-to-end expertise in modern Generative AI, Large Language Models (LLMs), Agentic workflows, and cloud-native ML infrastructure (Databricks / Azure). In this role, you will architect, evaluate, and productionize multi-agent systems, advanced Retrieval-Augmented Generation (RAG) pipelines, and customized foundational models for Fortune 500 enterprise clients.
Key Responsibilities
Agentic AI & Architectures: Design and deploy multi-agent systems using frameworks like LangGraph, AutoGen, CrewAI, or Semantic Kernel to automate multi-step enterprise workflows, tool invocation, and autonomous reasoning.
GenAI & LLM Solutions: Develop scalable RAG systems, advanced vector search strategies, hybrid indexing, and context-aware retrieval solutions. Apply fine-tuning techniques (PEFT, LoRA/QLoRA) and prompt optimization for domain-specific applications.
Databricks ML & Lakehouse Integration: Build data prep pipelines, orchestrate workflows, and register/deploy models via Databricks Mosaic AI, MLflow, Unity Catalog, and Databricks Model Serving.
Evaluation & Governance: Establish rigorous evaluation frameworks (RAGAS, TruLens, DeepEval) tracking faithfulness, latency, token spend, guardrails (NeMo, Llama Guard), and hallucination mitigation.
Production MLOps & Deployment: Collaborate with Data and DevOps engineers to expose models as low-latency APIs (FastAPI/Docker) hosted on Azure or AWS cloud infrastructure.
Leadership & Strategy: Mentor mid-level and junior data scientists, run client architectural deep-dives, and contribute reusable frameworks to Celebal’s AI Center of Excellence.
Required Skills & Experience
Experience: 5+ years of overall Data Science / ML experience, with 2+ years explicitly hands-on with LLMs, RAG, and Agentic AI frameworks.
Databricks Proficiency: Strong experience developing in the Databricks Lakehouse ecosystem (Delta Lake, MLflow, Unity Catalog, Databricks Model Serving).
GenAI Tooling: Advanced mastery of LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, and open/closed model APIs (OpenAI, Anthropic, Azure OpenAI, Mistral, LLaMA).
Vector Databases: Hands-on experience with vector stores such as Databricks Vector Search, Azure AI Search, Pinecone, Milvus, or Qdrant.
Languages & Foundations: Production-grade Python (async programming, OOP, design patterns), SQL, PyTorch/TensorFlow, and Git-driven CI/CD.
Cloud Platforms: Prior experience with Microsoft Azure (Azure OpenAI Service, Cognitive Services, Azure Machine Learning) or AWS.
Preferred Qualifications
Databricks Certified Machine Learning Professional or Generative AI Engineer certification.
Microsoft Certified: Azure AI Engineer Associate (AI-102).
Demonstrated experience optimizing inference pipelines (vLLM, Ollama, TensorRT-LLM) or implementing Graph-based RAG.
What We Offer
Work on high-impact GenAI customer deployments across healthcare, retail, manufacturing, and BFSI sectors.
Access to state-of-the-art enterprise cloud compute, model catalogs, and innovation labs.
Continuous learning with industry certifications and exposure to top-tier enterprise AI conferences.

Work arrangement
No

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