Spotify

Spotify

Staff Machine Learning Engineer - Music Mission

New York, NY · Staff+

Sponsorship not specified$227k-$325kDetected 22 days ago
PythonJavaScalaAlgorithmsMachine LearningData ScienceMLOpsA/B TestingUX ResearchResearchLeadershipMentoring

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level IV · 4×
Level I$109,8451 entry
Level II$137,7172 entries
Level III$165,5893 entries
Level IV$193,4614 entries

This range already reaches Level IV — the maximum four lottery entries.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · 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

  • is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale.
  • The DISCO Product Area is focused on building promotional tools that help artists reach more fans.
  • Our products serve artists at scale through Spotify for Artists, and we're building on the momentum of Discovery Mode to help artists and their teams find new listeners when it matters most.

Responsibilities

  • Collaborate with user research, design, data science, product management, and engineering to build new product capabilities that strengthen connections between artists and fans.
  • You care about reliable software, data-informed development, disciplined experimentation, and building systems that perform effectively at scale.
  • You communicate technical decisions and risks clearly and can build alignment with senior technical leaders and cross-functional partners.

Requirements

  • You can set technical direction for complex ML problems while remaining close to implementation and delivery.
  • You are comfortable navigating ambiguity, evaluating trade-offs, and creating clarity on high-impact initiatives.
  • 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 $227,495.00 - $324,993 USD, plus equity.

Benefits

  • Help define and drive the Machine Learning engineering strategy for Discovery Mode and related royalty programs, translating product goals into scalable technical solutions.
  • Design, build, evaluate, ship, and refine production Machine Learning systems through hands-on development.
  • Drive experimentation, optimization, testing, and tooling that improve the quality, reliability, and effectiveness of our Machine Learning systems.
  • Partner with engineers and Machine Learning practitioners across Spotify, including Music Tech Research and Personalization, to explore and develop new approaches to music promotion.
  • You have deep experience with Machine Learning and a strong understanding of Machine Learning algorithms, modeling approaches, evaluation, and experimentation.
  • You have hands-on experience designing and implementing production Machine Learning systems at scale using languages such as Python, Java, Scala, or similar.

Company info

  • Where You'll Be - 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.
  • Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators.
  • Prototype new approaches and turn successful ideas into reliable, scalable solutions for Spotify for Artists customers.
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This listing is sourced directly from Spotify's careers page and normalized into a canonical job model.