Back
Tier-1 brand, remote role, and mid-level ML generalist profile increase applicant competition.
Specialized ML and LLM production experience makes background fit highly domain-sensitive.
Explicit 2+ years requirement plus mandatory production ML/LLM and Python skills imply high strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and enhance a unified orchestration layer managing state transitions, context sharing, and intent routing across vendor and internal large language model (LLM) frameworks in a distributed conversational AI environment.
Build production-grade Python services integrating advanced AI and ML capabilities into customer-facing chatbot and agent support products.
Lead ML projects from design to delivery, collaborating cross-functionally to ensure scalable, secure, and high-performance AI-enabled experiences.
Minimum 2 years professional experience in machine learning and software engineering with production-grade ML service delivery.
Strong proficiency in Python and experience with modern AI architectures including LLMs and deep learning; familiarity with tools like LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock.
Working knowledge in at least one domain such as NLP, information retrieval, computer vision, or statistical modeling.
Work Experience Required: Minimum 2 years; Notice Period: Not explicitly mentioned in the JD.
Experienced in designing and implementing complex ML systems for conversational AI with cross-functional stakeholder collaboration.
Comfortable working on hybrid vendor-internal AI orchestration to build measurable and scalable chatbot solutions.
Operates well in a fast-paced, technically challenging environment focused on AI/ML-driven customer support platforms.