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Senior Data Scientist – Generative AI

6 years

15 - 17 Lacs

India

Posted:4 days ago| Platform: Linkedin logo

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Skills Required

data ai power retrieval finance healthcare security design ml architecture etl governance training aws testing jmeter model latency leadership drive documentation python engineering evaluation sagemaker shipping cataloging sparql containerization automation gitlab stack scripting angular js prototyping orchestration flex schedule learning experimentation research javascript management

Work Mode

Remote

Job Type

Full Time

Job Description

Note: This is a remote role with occasional office visits. Candidates from Mumbai or Pune will be preferred

About The Company

Operating at the intersection of

Artificial Intelligence, Cloud Infrastructure, and Enterprise SaaS

, we create data-driven products that power decision-making for Fortune 500 companies and high-growth tech firms. Our multidisciplinary teams ship production-grade

generative-AI and Retrieval-Augmented Generation (RAG)

solutions that transform telecom, finance, retail, and healthcare workflows—without compromising on scale, security, or speed.
Role & Responsibilities
  • Build & ship LLM/RAG solutions: design, train, and productionize advanced ML and generative-AI models (GPT-family, T5) that unlock new product capabilities.
  • Own data architecture: craft schemas, ETL/ELT pipelines, and governance processes to guarantee high-quality, compliant training data on AWS.
  • End-to-end MLOps: implement CI/CD, observability, and automated testing (Robot Framework, JMeter, XRAY) for reliable model releases.
  • Optimize retrieval systems: engineer vector indices, semantic search, and knowledge-graph integrations that deliver low-latency, high-relevance results.
  • Cross-functional leadership: translate business problems into measurable ML solutions, mentor junior scientists, and drive sprint ceremonies.
  • Documentation & knowledge-sharing: publish best practices and lead internal workshops to scale AI literacy across the organization.

Skills & Qualifications

  • Must-Have – Technical Depth: 6 + years building ML pipelines in Python; expert in feature engineering, evaluation, and AWS services (SageMaker, Bedrock, Lambda).
  • Must-Have – Generative AI & RAG: proven track record shipping LLM apps with LangChain or similar, vector databases, and synthetic-data augmentation.
  • Must-Have – Data Governance: hands-on experience with metadata, lineage, data-cataloging, and knowledge-graph design (RDF/OWL/SPARQL).
  • Must-Have – MLOps & QA: fluency in containerization, CI/CD, and performance testing; ability to embed automation within GitLab-based workflows.
  • Preferred – Domain Expertise: background in telecom or large-scale B2B platforms where NLP and retrieval quality are mission-critical.
  • Preferred – Full-Stack & Scripting: familiarity with Angular or modern JS for rapid prototyping plus shell scripting for orchestration.
Benefits & Culture Highlights
  • High-impact ownership: green-field autonomy to lead flagship generative-AI initiatives used by millions.
  • Flex-first workplace: hybrid schedule, generous learning stipend, and dedicated cloud credits for experimentation.
  • Inclusive, data-driven culture: celebrate research publications, OSS contributions, and diverse perspectives while solving hard problems together.
Skills: data,modern javascript,cloud,vector databases,angular,pipelines,ci,containerization,ml,aws,langchain,shell scripting,mlops,performance testing,knowledge-graph design (rdf/owl/sparql),feature engineering,ci/cd,python,aws services (sagemaker, bedrock, lambda),synthetic-data augmentation,generative ai,data-cataloging,metadata management,lineage,data governance

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