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Metro ML role with generalist LLM skills and established employer, resulting in moderate competition.
Specialized LLM and RAG skills favor AI-focused backgrounds but are moderately transferable.
Multiple specific LLM, RAG, and tooling requirements imply moderate filtering on technical skills.
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Develop, fine-tune, and deploy Large Language Models (LLMs) and Generative AI solutions using Python libraries like Hugging Face Transformers and OCI SDK for domain-specific adaptations.
Implement NLP techniques including sentiment analysis, entity extraction, text classification, and apply Retrieval-Augmented Generation (RAG) using vectorization and embedding with OpenSearch and Oracle Database 23ai vector capabilities.
Design and manage advanced prompt engineering, content moderation (PII detection, toxicity scoring), context retention for multi-turn interactions using Redis caching, and orchestrate tools including function calling and custom API endpoints for multi-stage AI workflows.
Bachelor's degree in Computer Science, Information Technology, or related field.
Proficiency in Large Language Models (LLMs), Generative AI, Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG).
Experience with Python libraries like Hugging Face Transformers, OCI SDK, and Database tools such as OpenSearch and Oracle Database 23ai's vector capabilities.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with practical implementation and fine-tuning of domain-specific LLMs and generative AI models in production environments.
Strong background in advanced NLP tasks and techniques, including sentiment analysis, entity extraction, prompt engineering, and managing multi-turn dialogues with session context retention.
Ability to orchestrate complex AI workflows involving various tools, APIs, and databases within enterprise or consulting settings.