Music Content Operations AIML Program Lead

A job at Apple is unlike any other youve had. Youll be challenged. Youll be inspired. And youll be proud. nnApple Music is looking for a Music Content Operations AIML Program Lead to help drive our strategic initiative to scale music content operations through models agents and automation. Youll lead the transition of music curation from a primarily manual operation toward a hybrid system where agents handle day-to-day work and human expertise is focused where it matters most high-priority high-risk and quality-critical decisions. This is a full-time individual contributor role on our Content Operations team reporting into Music Content Operations leadership. nnSitting at the intersection of operations and advanced technology youll serve as the technical liaison between our operational workflows and the data science and engineering teams building the models tools and agentic systems that scale this work far beyond what manual review can achieve alone. Youll partner with engineering to develop agents help establish the key infrastructure to support and integrate them and define how humans stay in the loop as that infrastructure matures. Youll translate messy operational reality everything from track-level metadata quirks to editorial judgment calls into crisp technical requirements evaluate the solutions that come back and decide what ships.

Own the strategy and execution plan to scale curation through models agents and automation sequencing workstreams by impact and driving them from concept to production. Partner with Engineering and Data Science to develop agents that take on day-to-day curation work from defining requirements through evaluation and production rollout. Help establish the key infrastructure to support integrate and orchestrate agents over time shaping how agentic systems plug into existing curation workflows and data. Define the future operating model for curation determining where agents handle work autonomously and where humans stay in the loop for high-priority high-risk or quality-assessment cases including review of agent output. Translate operational challenges into clear actionable specifications that engineering and data science teams can execute against. Break down ambiguous problems into well-scoped prioritized workstreams sequenced by impact. Start with the highest-leverage slice; iterate from there. Evaluate technical proposals and model outputs participate in design reviews and build eval frameworks (golden sets quality metrics error analysis human-in-the-loop feedback) to judge whether AI/ML and agentic solutions are ready for production. Design and iterate on human-in-the-loop tooling that surfaces agent and model outputs (confidence scores candidate matches suggested labels risk signals) so reviewers can validate high-stakes decisions with speed and accuracy. Run ROI and impact analyses to distinguish short-term tactical wins from long-term structural solutions and to prioritize where automation delivers the most leverage. Communicate upward build clear compelling narratives and decks and present progress tradeoffs and recommendations to senior leadership. Partner cross-functionally with Engineering Data Science Product Editorial Analytics and peer Operations teams (including Artist Curation Shazam Operations Partner Operations and Data Strategy) to surface interdependencies and align priorities.

The right person for this role is a rare combination of technically fluent and deeply detail-oriented someone who thinks in systems moves with urgency and knows how to get things done across complex cross-functional energized by ambiguity. Apple is known for operating at the edge of whats defined and you know how to navigate without a map making progress while the picture is still prioritize ruthlessly. You instinctively ask Whats the highest-impact thing I could solve first before touching anything comfortable holding a multi-year vision while executing this weeks an independent operator who moves forward with light direction but knows when to pull others have exceptional attention to detail the kind that catches metadata anomalies mislabeled tracks or subtle content-risk signals others communicate precisely and persuasively in writing in decks and in the room with have technical fluency comfortable discussing system design data pipelines MLOps agentic architectures and model evaluation and the real-world challenges of deploying AI/ML solutions without needing to be the one writing the have a tinkerers mentality. Youre not afraid to try things fail quickly and pivot. Youd rather ship a rough prototype this week and learn from it than design the perfect solution for three lead through influence. You build trust across organizational boundaries and with vendor partners and get things done without relying on direct reporting lines.

5 years in operations program management or technical product roles with meaningful exposure to AI/ML-driven experience translating operational or product problems into ML requirements and working directly with data scientists and engineers through model development to LLM-based workflows prompt evaluation or agentic automation particularly applied to content moderation classification or operational familiarity with content classification and content-risk tradeoffs sufficient to judge where human review is track record of managing multiple concurrent workstreams with consistent on-time delivery and proactive stakeholder evaluating model outputs designing eval sets quality metrics error analysis and human feedback designing or specifying review/annotation tooling that surfaces AI inputs to human understanding of core analytics principles (sampling hypothesis testing statistical measurement).nProven ability to produce executive-ready written narratives and record of leading ambiguous initiatives end-to-end with minimal experience handling sensitive and confidential information with integrity and discretionnAbility to be onsite; this role is an in-person onsite positionnAvailable to work some nights and weekends as needednUp to 15% travel required; both domestic and international

Experience in the music industry or with music metadata catalogs rights data genre taxonomies or editorial/streaming -on experience building or deploying agentic systems in collaborating with international querying data (SQL or similar) to investigate catalog issues or comparable BI genuine passion for music and curiosity about the systems that power the modern music degree in Engineering Business/Economics or equivalent experience.