Spotify
Senior Product Quality Analyst - AI Voice
New York, NY · Senior
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odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
$15,868 more — $130,354 — moves this role to Level III and 3 lottery entries. That figure is inside the range the employer already advertised.
Based on the DOL prevailing wage for this occupation and worksite, a base salary of $130,354 would place this position at wage Level III. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Quality Assurance Analysts and Testers" for prevailing-wage purposes.
DOL prevailing wage, 2026-27 wage year · Software Quality Assurance Analysts and Testers (15-1253) · New York-Newark-Jersey City, NY-NJ. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- The Personalization team makes deciding what to play next easier and more enjoyable for every listener.
- From Blend to Discover Weekly, we're behind some of Spotify's most-loved features.
- We built them by understanding the world of music and podcasts better than anyone else.
Responsibilities
- Own the quality bar for Spotify's AI voice models, defining what "good enough" means for different products, audiences, languages and use cases.
- Independently design evaluation rubrics and build an evaluation approach that measures qualities such as naturalness, tone, pacing, pronunciation, accent, audio quality and overall experience.
- Benchmark Spotify's AI voices against third-party models and competitors to understand where our experiences lead, where they differ and where there are opportunities to improve.
- We think about AI voices from a casting perspective - including voice type, age and gender - and from a performance perspective, recognizing that a voice may need to perform differently for DJ than it does for an audiobook recap.
- You'll own how we define and measure AI voice quality, bringing together Voice Production's creative bar, Speak's technical bar and the wider industry bar.
- You communicate clearly across creative, technical and product teams and can act as a reliable point of contact for internal partners and external vendors.
Requirements
- You have experience in product quality, evaluation, data curation or a closely related field where human judgment is used to assess model or product performance.
- You know how to independently define evaluation criteria and turn subjective qualities into clear, repeatable rubrics.
- You are comfortable designing and running both qualitative and MOS-style evaluations and synthesizing the results into actionable insights.
- You are comfortable working autonomously, identifying what needs to be evaluated and establishing the processes and cadence to make that evaluation useful over time.
- You are curious about generative AI, speech technology and the evolving AI voice landscape and can translate changes in the industry into meaningful benchmarks for Spotify.
- You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones.
Compensation
- The United States base range for this position is $114,486–$163,552 USD, plus equity.
Benefits
- Partner closely with voice experts, machine learning teams, product partners and vendors to maintain a consistent quality bar across demanding and sometimes competing priorities.
Company info
- We are the Voice Production Team, the creative team behind Spotify's AI voice experiences.
- Where You'll Be - This role is based in New York or Los Angeles. - We offer you the flexibility to work where you work best!
- At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone.
This listing is sourced directly from Spotify's careers page and normalized into a canonical job model.