Music Content Operations AIML Program Lead

The Digital Asset Management Consortium, Inc.; Cupertino (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Apple is seeking a Music Content Operations AIML Program Lead in Cupertino to drive scaling of music curation through models, agents, and automation. You will define the future operating model for curation, balance agentic automation with human review, and translate operational challenges into actionable specs for engineering and data science teams.

You will own the strategy and execution plan to scale curation, partner with Engineering and Data Science to deploy agents, and shape how agentic

Qualifications

• 5+ years in operations, program management, or technical product roles with AI/ML‑driven workflows.
• Experience translating operational or product problems into ML requirements and working with data scientists/engineers.
• Exposure to LLM‑based workflows, prompt evaluation, or agentic automation in content moderation or workflows.
• Understanding content classification and content‑risk tradeoffs to judge when human review is needed.
• Experience managing multiple concurrent workstreams with on‑time delivery and stakeholder communication.
• Experience evaluating model outputs with eval sets, metrics, and human feedback loops.
• Designing or specifying review tooling that surfaces AI inputs to human reviewers.
• Familiarity with core analytics principles like sampling and hypothesis testing.
• Executive‑ready written narratives and presentations.
• Leading ambiguous initiatives end‑to‑end with minimal direction.
• Handling sensitive information with integrity and discretion
• Ability to be onsite; this role is an in‑person, onsite position
• Willingness to work some nights and weekends; up to 15%+ travel (domestic/international)

Responsibilities

• Translate operational challenges into actionable specifications for engineering and data science teams.
• Break down problems into well‑scoped, prioritized workstreams sequenced by impact.
• Evaluate proposals and model outputs; participate in design reviews and establish evaluation frameworks.
• Design human‑in‑the‑loop tooling showing AI outputs, confidence scores, and risk signals for reviewers.
• Lead ROI and impact analyses to distinguish short‑term wins from long‑term solutions.
• Communicate progress, tradeoffs, and recommendations to senior leadership.
• Partner with Engineering, Data Science, Product, Editorial, Analytics, and Operations teams to surface interdependencies.

Skills

AI/ML workflows

Prompt evaluation

LLM‑based workflows

Content classification

Executive storytelling

Ambiguity navigation

Cross‑functional leadership

Education

Bachelor's degree in Engineering, Business/Economics, or equivalent experience

Tools

SQL

Tableau

Job description

Music Content Operations AIML Program Lead

Apple 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. You'll 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.

Sitting at the intersection of operations and advanced technology, you'll 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. You'll 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. You'll 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.

Responsibilities

• 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 environments.
• You're energized by ambiguity. Apple is known for operating at the edge of what's defined, and you know how to navigate without a map — making progress while the picture is still forming.
• You prioritize ruthlessly. You instinctively ask, "What's the highest‑impact thing I could solve first?" before touching anything else.
• You're comfortable holding a multi‑year vision while executing this week's priorities.
• You're an independent operator who moves forward with light direction but knows when to pull others in.
• You have exceptional attention to detail — the kind that catches metadata anomalies, mislabeled tracks, or subtle content‑risk signals others miss.
• You communicate precisely and persuasively, in writing, in decks, and in the room with leadership.
• You 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 code.
• You have a tinkerer's mentality. You're not afraid to try things, fail quickly, and pivot. You'd rather ship a rough prototype this week and learn from it than design the perfect solution for three months.
• You lead through influence. You build trust across organizational boundaries and with vendor partners, and get things done without relying on direct reporting lines.

Minimum Qualifications

• 5+ years in operations, program management, or technical product roles with meaningful exposure to AI/ML‑driven workflows.
• Demonstrated experience translating operational or product problems into ML requirements and working directly with data scientists and engineers through model development cycles.
• Exposure to LLM‑based workflows, prompt evaluation, or agentic automation — particularly applied to content moderation, classification, or operational workflows.
• Conceptual familiarity with content classification and content‑risk tradeoffs, sufficient to judge where human review is warranted.
• Demonstrated track record of managing multiple concurrent workstreams with consistent on‑time delivery and proactive stakeholder communication.
• Experience evaluating model outputs — 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 (sampling, hypothesis testing, statistical measurement).
• Proven ability to produce executive‑ready written narratives and presentations.
• Track record of leading ambiguous initiatives end‑to‑end with minimal direction.
• Direct experience handling sensitive and confidential information with integrity and discretion
• Ability to be onsite; this role is an in‑person, onsite position
• Available to work some nights and weekends as needed
• Up to 15%+ travel required; both domestic and international

Preferred Qualifications

• Experience in the music industry or with music metadata, catalogs, rights data, genre taxonomies, or editorial/streaming products.
• Hands‑on experience building or deploying agentic systems in production.
• Experience collaborating with international stakeholders.
• Comfort querying data (SQL or similar) to investigate catalog issues independently.
• Tableau or comparable BI tooling.
• A genuine passion for music and curiosity about the systems that power the modern music industry.
• Bachelor's degree in Engineering, Business/Economics, or equivalent experience.

Employer: Apple

Location: Cupertino, CA, USA

Type: Full‑Time