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Mid-level ML role in Bangalore with broad LLM skillset attracts moderate competition.
Core ML and LLM skills transfer across industries, though life-sciences preference adds moderate domain specificity.
Explicit 6+ years plus mandatory LLM, RAG, LangChain, production and backend skills enforce strict filtering.
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Lead end-to-end AI/ML lifecycle activities including ideation, research, data engineering, model development, evaluation, deployment, and scaling in life sciences and healthcare domains.
Architect, build, and deploy advanced AI solutions such as LLM-powered services, Retrieval-Augmented Generation (RAG), agentic workflows, and Generative AI integrations using tools like LangChain and LangGraph.
Mentor engineers, influence AI/ML platform strategy, implement evaluation frameworks, and ensure production-grade, scalable AI solutions impacting scientific workflows and customer outcomes.
Bachelor's degree in AI/ML, computer science, statistics, engineering, or related technical field; Master's preferred.
6+ years industry experience in software engineering and deploying AI/ML production systems; 4+ years agile/scrum experience.
Hands-on expertise in AI techniques including deep learning, RAG, agentic AI, Python, PyTorch, C++, C#, LangChain, LangGraph, and backend engineering best practices.
Strong data engineering skills and experience with deployment infrastructure and production integration; work schedule: Mon-Fri office role.
Experienced technical individual contributor with proven leadership in architecting and delivering production AI/ML systems at scale in regulated science domains like life sciences, genomics, or healthcare.
Proficient in deploying LLM and Generative AI solutions integrating complex workflows and evaluation-driven iterative improvements.
Collaborates effectively with cross-functional teams including data scientists, product managers, and engineers, capable of influencing AI adoption and standards across an organization.