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Tier-1 brand, remote role, and mid-level ML generalist profile increase competition.
Specialized ML/LLM production expertise limits cross-industry transferability.
Explicit 5+ years, mandatory production ML/LLM experience and specific frameworks enforce high shortlisting strictness.
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Architect and deploy a sophisticated orchestration layer managing state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational AI environment.
Develop and maintain production-grade Python services integrating advanced ML/AI research into scalable customer-facing products with measurable performance.
Lead end-to-end execution of complex ML projects, including design reviews, establishing best practices, mentoring engineers, and ensuring security, scalability, and performance.
Minimum 5+ years of professional experience in machine learning and software engineering with a track record of shipping production-grade ML services at scale.
Expertise with modern AI architectures (LLMs, deep learning) and generative AI frameworks such as LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock.
Deep proficiency in Python with proven ability to write clean, maintainable, and highly-tested production code.
Specialized knowledge in at least one of the following domains: NLP, information retrieval, computer vision, or advanced statistical modeling.
Experienced in architecting complex hybrid conversational AI systems blending vendor AI, internal multi-agent systems, and human interaction management.
Skilled in bridging advanced ML research with reliable, scalable production systems focusing on measurable outcomes and operational reliability.
Effective at technical leadership including writing design documents, conducting architecture reviews, mentoring engineers, and communicating complex concepts to cross-functional stakeholders.