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Vrinda International

Vrinda International

DATA SCIENTIST

Gurugram, Delhi NCR, INPresencialContratoTempo integral

Publicado 16 de set. de 2026

Esta vaga foi publicada em EN

WE ARE HIRING | DATA SCIENTIST

Location: Gurugram, Delhi NCR

Experience: 3–4 Years | Relevant Data Scientist experience: 3+ Years

CTC: Up to ₹25 LPA

Work Mode: Work From Office

Shift: 9:00 AM – 6:00 PM

Notice Period: Immediate to 15 Days Only

We are looking for Data Scientists with strong Python, AI/ML and production AI application experience.

KEY SKILLS:

  • Strong Python & software engineering fundamentals
  • AI/ML application development
  • RAG architectures & LLM workflows
  • AI system design, evaluation & monitoring
  • Production AI deployment & maintenance
  • TensorFlow / PyTorch / Scikit-learn
  • NLP concepts
  • API development & integration
  • Debugging, testing & performance optimization

GOOD TO HAVE:

  • Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB
  • AWS / Azure / GCP
  • Docker & deployment pipelines
  • Fintech domain experience

KEY RESPONSIBILITIES:

  • Design scalable, reliable and production-ready AI systems
  • Build and maintain RAG pipelines and AI agent frameworks
  • Develop reliable LLM workflows using retrieval, validation and business rules
  • Perform model evaluation, data analysis and performance optimization
  • Develop APIs and integrate AI solutions with existing platforms
  • Conduct root-cause analysis and improve AI pipeline accuracy and reliability
  • Monitor, troubleshoot and continuously improve deployed AI systems
  • Collaborate with engineering and business teams to deliver AI solutions

INTERVIEW PROCESS:

L1 – Technical Assessment

L2 – Technical Round

L3 – Technical Round

L4 – Managerial + HR Interview

Resumo da função

Tipo de vaga

Tempo integral

Competências necessárias

Python programmingSoftware engineering fundamentalsAI/ML application developmentRAG architecture designLLM workflow developmentAI system designModel evaluation & performance optimizationProduction deployment & maintenance of AI systemsTensorFlow / PyTorch / Scikit-learnNLP conceptsAPI development & integrationVector databases (Pinecone, Weaviate, FAISS, ChromaDB)Cloud platforms (AWS / Azure / GCP)Docker & deployment pipelinesCross-functional collaboration (engineering & business teams)

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