Data Scientist

Pagaar India

India

On-site

INR 2,185,000 - 2,671,000

Full time

14 days+
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Job summary

Pagaar India is seeking an experienced Data Scientist Gen AI to design and deliver advanced AI/ML solutions using Generative AI technologies. The role focuses on building scalable applications powered by Large Language Models and RAG pipelines, with strong hands-on Python and SQL expertise.

The candidate will lead end-to-end AI development, from data prep and experimentation to production deployment, coordinating with cross-functional teams to translate business needs into practical AI solutions.

Qualifications

  • We are seeking an expert Data Scientist with deep Gen AI experience and hands-on ML skills.
  • Must have strong Python and SQL capabilities and knowledge of LLMs.
  • Experience building RAG pipelines and Agentic AI solutions is required.

Responsibilities

  • Design, develop, and deploy Generative AI and ML solutions for business use cases.
  • Build and deploy LLM-powered applications with state-of-the-art models.
  • Develop RAG pipelines and agentic AI workflows for production.
  • Implement data processing, feature engineering, and model development in Python/SQL.
  • Evaluate models, optimize performance, and ensure scalable AI pipelines.

Skills

Generative AI
LLMs
Python
SQL
RAG
Agentic AI
Embeddings
Vector databases

Tools

LLM frameworks
Vector databases
Embeddings tooling

Job description

Data Scientist Gen AI Location: Bangalore Experience: 48 Years CTC: 2428 LPA + 10% Variable Employment Type: Full-time

Job Summary

We are looking for an experienced Data Scientist Gen AI with 48 years of experience in Generative AI, Machine Learning, Python, SQL, LLMs, RAG, and Agentic AI . The ideal candidate will be responsible for designing and developing AI/ML solutions using modern Generative AI technologies and building intelligent, scalable applications powered by Large Language Models. The role requires strong hands‑on programming skills and the ability to translate business requirements into practical AI solutions.

Key Responsibilities
  • Design, develop, and deploy Generative AI and Machine Learning solutions for business use cases.
  • Build and implement LLM-powered applications using state-of-the-art models and frameworks.
  • Develop RAG (Retrieval-Augmented Generation) pipelines for knowledge-based AI applications.
  • Design and implement Agentic AI solutions , including AI agents capable of reasoning, tool use, and task execution.
  • Develop data processing, feature engineering, and model development workflows using Python and SQL .
  • Experiment with different LLMs, prompting strategies, embeddings, vector databases, and retrieval techniques.
  • Fine-tune and optimize AI/ML models where required.
  • Evaluate LLM outputs and improve model accuracy, relevance, reliability, and performance.
  • Develop and optimize AI pipelines for production environments.
  • Work with cross-functional teams to understand business requirements and translate them into AI solutions.
  • Conduct research and stay updated on emerging Gen AI, LLM, Agentic AI, and ML technologies.
  • Troubleshoot model, data, and application-level issues and continuously improve AI solutions.
  • Follow best practices related to AI development, data quality, security, scalability, and responsible AI.
Required Skills
  • 48 years of experience in Data Science / Machine Learning / AI .
  • Strong hands‑on experience with Generative AI and LLMs .
  • Strong programming skills in Python .
  • Strong knowledge of Machine Learning concepts and algorithms .
  • Hands‑on experience building RAG-based applications .
  • Practical experience with Agentic AI / AI Agents .
  • Strong understanding of LLM architecture, prompting, embeddings, and vector search .
  • Strong SQL skills and experience working with structured/unstructured data.
  • Experience developing and deploying AI/ML solutions.
  • Strong analytical, problem‑solving, and communication skills.
Preferred Skills
  • Experience with LLM frameworks and orchestration tools.
  • Experience with vector databases and semantic search.
  • Knowledge of model evaluation and LLM evaluation techniques.
  • Experience with fine‑tuning or adapting LLMs for specific use cases.
  • Understanding of cloud‑based AI/ML platforms.
  • Experience building production‑grade Gen AI applications.
  • Knowledge of AI/ML APIs and integration with enterprise applications.
Candidate Profile

The ideal candidate should be a hands‑on Gen AI Data Scientist with strong Python and ML fundamentals and practical experience building LLM, RAG, and Agentic AI solutions . Candidates should be comfortable working on end‑to‑end AI problems, from data preparation and experimentation to application development and production deployment.

Key Skills

Key Skills: Generative AI | Gen AI | Python | Machine Learning | LLM | RAG | Agentic AI | AI Agents | SQL | Data Science

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