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Metro mid-level ML role at a known multinational but niche GenAI requirements moderate candidate competition.
Core GenAI/LLMOps skills are transferable, though biopharma/regulatory experience increases specificity.
Explicit 5+ years, mandatory GenAI/LLM depth, and regulated-domain experience make filters stringent.
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Lead design and deployment of enterprise-level GenAI and advanced ML solutions including LLM applications, fine-tuning, and agentic workflows from prototype to production.
Drive technical standards, architecture decisions, and governance including evaluation, hallucination mitigation, and responsible AI practices in a regulated environment.
Mentor junior data scientists, collaborate cross-functionally with stakeholders, and manage delivery priorities in a complex matrixed setting.
5+ years of applied data science/machine learning experience with strong hands-on expertise in GenAI (LLMs, RAG, fine-tuning, agentic workflows).
MS or PhD in a quantitative discipline (PhD preferred).
Experience deploying ML/GenAI solutions in production on cloud platforms (AWS or Azure) with LLMOps/MLOps practices.
Preferred domain experience in biopharma/healthcare and knowledge of regulated environments (GxP, 21 CFR Part 11).
Senior technical leader comfortable owning complex end-to-end GenAI model lifecycles including architecture, governance, and production deployment.
Experienced in translating ambiguous, high-impact problems into measurable solutions with strategic stakeholder alignment and executive communication.
Proficient in advanced ML/statistical methods, experimental design, and collaborating across business, engineering, and domain teams within regulated, high-stakes environments.