Lead, ML Data Operations

We're building the world's first creative entertainment platform, where the entire world can feel the joy and fulfillment of making music. Music is for everyone: Our users include everyone from grandmothers creating songs for their loved ones, to Grammy winners using Suno Studio, our power tool, to make the most popular hits in the world.

Building the future of entertainment requires ambition. The pace is fast, the problems are hard, and the work demands ownership and intensity. For the right people, it’s incredibly rewarding: a chance to shape a new medium, work with a small team that cares deeply about quality, make music, drink too much coffee, and build something that millions of people use to express themselves in ways that were never before possible.

Suno is the fastest growing consumer entertainment company and the leader in AI music. We are backed by leading investors including Bond Capital, Menlo Ventures, Lightspeed Venture Partners, IVP, Forerunner, Union Square Ventures, Alkeon, Quiet, Matrix Partners, Schroders Capital and, NVentures (venture arm of NVIDIA).

We're looking for a Lead of ML Data Operations to build and lead a new function at Suno. This team owns how we source and develop the data that powers our models. You’ll work closely with Research and Product to understand what's needed and figuring out how to deliver it, whether through external partners, in-product collection, or both. You’ll also build this function from the ground up so expect real ownership and real ambiguity in equal measure!

• Source, evaluate, and manage relationships with external data labeling vendors, from initial scoping through contracts, quality oversight, and ongoing performance

• Partner with ML researchers to understand data requirements and develop concrete plans to meet them

• Identify opportunities to improve how Suno collects data with product and engineering

• Build and lead the team, systems, and processes that make data sourcing a reliable, repeatable capability

• Contribute to a data-driven model development culture as part of a close-knit team of researchers, engineers, and product builders

• Support our mission of making creative fulfillment a daily reality for everyone

• 6–8+ years of experience in ML data operations, training data, or data labeling programs with direct experience managing external labeling vendors, building internal labeling systems, or both

• Demonstrated leadership at a director or equivalent level, with a track record of building teams or functions that didn't previously exist

• Comfort and excitement with operating with a high degree of autonomy where the path isn't fully defined

• Strong cross-functional instincts across Research, Product, and Engineering

• Background at a foundational model company or data labeling organization

• Experience influencing how product features are designed with training data collection in mind

• Familiarity with music, audio, or creative AI

This role is expected to work from the designated Suno office 5 days a week, per Suno's company policy. Full-time employees will receive competitive equity packages, and comprehensive benefits. The actual base salary offered may vary depending on location, skills, qualifications, and experience.

Applicants must be eligible to work in the US.

• Company Equity Package

• 401(k) with 3% Employer Match & Roth 401(k)

• Medical, Dental, & Vision Insurance (PPO w/ HSA & FSA options)

• 11 Paid Holidays + Unlimited PTO & Sick Time

• 16 Weeks of Paid Parental Leave

• Creative Education Stipend

• Generous Commuter Allowance

• In-Office Lunch (5 days per week)

Suno is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the Massachusetts Fair Chance in Employment Act, NYC Fair Chance Act, LA City Fair Chance Ordinance, and San Francisco Fair Chance Ordinance.