Job Description

Key Responsibilities:

  • Build and deploy end-to-end ML & LLM pipelines
  • Develop RAG systems and multi-agent AI workflows
  • Manage model lifecycle (experiment → registry → production)
  • Containerize and deploy using Docker & Kubernetes
  • Implement CI/CD pipelines for ML/AI systems
  • Monitor model performance, drift, and reliability in production
  • Collaborate with data scientists to productionize models
  • Integrate AI solutions into scalable enterprise platforms

Core Tech Skills:

  • Strong Python (production-grade, scalable code)
  • MLOps: MLflow / Weights & Biases, model registry & lifecycle
  • LLMs & GenAI: OpenAI / open-source models, embeddings, RAG , agentic workflows
  • AI Frameworks: LangChain / LlamaIndex (or simi...

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