Music Content Operations AIML Program Lead

What you'll do

• Own the strategy and execution plan to scale music curation through models, agents, and automation.
• Translate operational challenges and metadata quirks into clear technical requirements for engineering and data science teams.
• Partner with engineering to develop, evaluate, and roll out agentic systems for day-to-day curation work.
• Define the operating model for human-in-the-loop systems to handle high-priority and high-risk decisions.
• Build evaluation frameworks including golden sets, quality metrics, and error analysis to judge model readiness.
• Design human-in-the-loop tooling to surface agent outputs like confidence scores and risk signals for reviewers.
• Run ROI and impact analyses to prioritize automation workstreams based on long-term structural leverage.
• Create executive-ready narratives and presentations to communicate progress, tradeoffs, and recommendations to senior leadership.

What we're looking for

• 5+ years of experience in operations, program management, or technical product roles with exposure to AI/ML-driven workflows.
• Demonstrated experience translating operational or product problems into ML requirements and working with data scientists and engineers.
• Experience with LLM-based workflows, prompt evaluation, or agentic automation for content moderation, classification, or operational workflows.
• Experience evaluating model outputs by designing eval sets, quality metrics, error analysis, and human feedback loops.
• Experience designing or specifying review/annotation tooling that surfaces AI inputs to human reviewers.
• Conceptual understanding of core analytics principles including sampling, hypothesis testing, and statistical measurement.
• Proven ability to produce executive-ready written narratives and presentations while leading ambiguous initiatives end-to-end.
• Bachelor's degree in Engineering, Business/Economics, or equivalent experience (preferred).