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Mid-level ML role in Bangalore with popular title and metro demand, yielding moderate competition.
Deep ML/NLP and production MLOps focus gives moderate cross-industry transferability.
Requires 6+ years, production ML, LLM/NLP and cloud MLOps skills, increasing strictness.
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Own end-to-end machine learning problems including data exploration, modeling, deployment, monitoring, and iteration in production at enterprise scale.
Build NLP, LLM, agentic systems, and ranking/recommendation models that are explainable and integrate into customer-facing AI products and APIs.
Collaborate with Product and Go-to-Market teams to translate ambiguous business problems into shipped, scalable AI solutions and improve ML platform architecture.
6+ years of industry experience building and deploying machine learning systems with clear end-to-end ownership.
Strong expertise in NLP, transformers, embeddings, retrieval systems, and practical experience with modern GenAI tooling (e.g., LangGraph, LangChain, Amazon Bedrock).
Proficient in Python; experience with distributed ML pipelines on cloud infrastructure like AWS or Databricks.
Work Experience Required: 6+ years; other hard requirements: Not explicitly mentioned in the JD regarding degree or location; Notice period: Not explicitly mentioned.
Experienced in building production-grade, explainable ML models for enterprise AI products, especially with NLP and retrieval-based architectures.
Comfortable translating ambiguous technical and business problems into deployed AI capabilities with a product impact focus.
Strong communicator able to partner cross-functionally and explain complex ML concepts to technical and non-technical stakeholders; willing to mentor engineers.