Lead, ML Data Operations
Suno · San Francisco, CA
$300,000–$360,000
Jul 15, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
A leadership role responsible for building and running a new ML data operations function from scratch at an AI music company. Day-to-day work involves sourcing and managing external data labeling vendors, partnering with ML researchers to define and fulfill training data needs, and identifying ways to improve in-product data collection. Best suited to someone with substantial ML data operations experience who has previously stood up teams or programs that did not previously exist.
Senior level · 6+ years · Boston-Cambridge-Newton, MA-NH · Full-time
Advertised as Principal, but the requirements read as Senior.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
Why we read it this way (6)
The role is titled 'Lead of ML Data Operations' — 'Lead' here signals a function-building leadership role rather than a standard IC or team-lead position, so advertised seniority is mapped to Principal. However, the actual scope (building one new team, director-equivalent level) is consistent with a Senior band rather than true org-wide Principal authority.
SOC classification is a genuine judgment call: this is primarily a people/function-building management role (11-3021), but the domain is ML data operations, which overlaps with 15-2051 (Data Scientists) and 15-1299. 11-3021 was chosen because the JD emphasizes team-building, vendor management, and cross-functional leadership over hands-on technical work.
Location is inferred as the Boston/Cambridge area based on Suno's known headquarters and the Massachusetts-specific legal references (Massachusetts Fair Chance in Employment Act) in the posting. No explicit city is named.
No compensation figures are stated; the posting only mentions 'competitive equity packages' and 'comprehensive benefits.'
Skills in this role are largely operational and managerial rather than named technologies; the few concrete skill areas listed (ML data ops, vendor management, training data) are retained. Nice-to-haves around foundational model company background and audio/music AI are listed under the 'Nice-to-Haves' section and are preferred only.
Ignored 3 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML data operations, data labeling vendor management, foundational model company experience.
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