Jobs / United States / Spotify

Spotify

Senior Staff Machine Learning Engineer - Content Platform

Remote (USA) · Remote · US only Posted today

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Skills this job asks for

Machine learningComplianceLeadershipPyTorchTensorFlow

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Where you can work from

United States only

Based on the listing's location: Remote (USA).

The company's headquarters is not the same as where you may work from. Visa sponsorship only matters if you would relocate; see below.

Visa sponsorship, if you would relocate

Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 79 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Spotify paid sponsored hires in similar roles3 certified filings for “MACHINE LEARNING ENGINEER II” (Computer and Information Research Scientists) in MA: $195k–$205k, median $200k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 79 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Spotify paid sponsored hires in similar roles
3 certified filings for “MACHINE LEARNING ENGINEER II” (Computer and Information Research Scientists) in MA: $195k–$205k, median $200k. Most were filed at wage level I (33%) — 1 lottery entry, ≈15% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

We design Spotify ’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is understood, trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continue to grow—driven by advances in AI, new creation tools, and emerging content formats—we’re investing in intelligent systems that can understand, evaluate, manage, and route content reliably at global scale. We’re hiring Senior Staff Machine Learning Engineers to build and scale foundational ML systems that power content understanding, safety, policy enforcement, and decisioning across Spotify. Depending on your experience and interests, you may focus on areas ranging from multimodal content understanding and platform-level ML systems to safety, risk detection, policy enforcement, and compliance. You’ll help shape the architecture and technical strategy behind how Spotify understands and makes decisions about content at global scale. This work is foundational to delivering safe, high-quality experiences for listeners and creators while enabling new ways for people to interact with content across Spotify. What You Will Do • Define and drive machine learning strategy across content understanding, safety, policy enforcement, and platform-level decisioning • Build and scale production ML systems for classification, moderation, ranking, risk detection, and content evaluation • Develop automated decisioning systems that support content quality, integrity, safety, and policy compliance at scale • Design and deploy ML systems across multiple content modalities, including text, audio, image, and video • Build systems capable of evaluating and making decisions about content in real time and at Spotify scale • Enable controlled and reliable access to content and metadata for downstream products and applications • Collaborate closely with Product, Policy, Trust & Safety, and Engineering teams to translate content standards into scalable technical solutions • Advance automation while maintaining high standards for quality, safety, fairness, explainability, and reliability • Provide technical leadership across teams, mentoring engineers and influencing ML engineering, evaluation, and system design best practices Who You Are • You have significant experience designing and building production-grade machine learning systems at scale • You have deep experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or similar • You have experience with—or a strong interest in—multimodal machine learning across areas such as text, audio, image, or video • You have built systems where machine learning outputs inform or automate real-world decisions • You understand how to balance automation with quality, safety, reliability, and user experience • You’re comfortable tackling complex and ambiguous technical problems with significant product and business impact • You think

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