Artist Curation Operations Lead
Location: Hybrid onsite in Cupertino, CA
Schedule: 40 hours
Duration: 12 months
Pay: $95-$97.86 DOE

The Planet Group is looking for an Artist Curation Operations Lead to join our well-known Fortune 500 client on a 12-months contract, working a hybrid onsite schedule in Cupertino, CA

Artist Curation Operations Lead | 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.
• 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.

• Experience in the music industry or with music metadata, catalogs, rights data, or artist-facing products.
• Familiarity with entity resolution / disambiguation problems (artists, works, identities).
• Exposure to LLM-based workflows, prompt evaluation, or agentic automation.
• Experience collaborating with international stakeholders or managing cross-cultural projects is a plus.
• Comfort querying data (SQL or similar) to investigate issues independently.
• Experience managing vendor or outsourced review teams.
• Tableau or comparable BI tooling.
• A genuine passion for music and curiosity about the systems that power the modern music industry.

Artist Curation Operations Lead | Description:

• Lead artist curation operations end-to-end -- covering artist pages, bios, images, disambiguation, and the expanding surface area of artist-facing data -- and serve as the primary operational owner and escalation point for vendor teams raising curation questions.
• Bridge communication between business stakeholders and technical teams (Data Science, Engineering, AI/ML), ensuring operational needs are clearly understood and technical tradeoffs are clearly communicated back.
• Translate operational challenges into technical requirements -- from artist disambiguation to image quality to bio accuracy -- into clear, actionable specifications that engineering and data science teams can execute against.
• Break down ambiguous problems like artist disambiguation 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 design eval frameworks (golden sets, quality metrics, error analysis, human-in-the-loop feedback) to judge whether AI/ML solutions are ready for production.
• Design and iterate on manual review tooling that surfaces AI-generated inputs (confidence scores, candidate matches, suggested actions) to accelerate reviewer throughput and accuracy.
• Identify opportunities to apply ML models, agentic workflows, and automation to pressing artist curation problems -- running lightweight ROI and impact analyses to distinguish short-term tactical wins from long-term structural solutions.
• Communicate upward -- build clear, compelling decks and present progress, tradeoffs, and recommendations to leadership.
• Partner cross-functionally with Engineering, Data Science, Product, Analytics, and peer Operations teams (including Partner Operations and Data Strategy) to surface interdependencies and align priorities.