Skills this job asks for
Machine learningA/B testingPythonLean / Six SigmaLLMs
Add your CV (free) to see which of these your CV is missing.
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
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. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
Growlithe is a fast-moving squad within Spotify's Conversation Product Area, focused on bringing emerging Search and agentic experiences to life. We explore, define, build, validate, and optimize new ideas to help listeners discover the content they love. Our work spans personalized Search, music video discovery and ranking, audiobook Search expansion, and the foundations of more social Search experiences.
We're looking for a Senior Machine Learning Engineer to help shape the next generation of Search at Spotify. You'll work at the intersection of machine learning, personalization, and product development, turning complex challenges into intuitive discovery experiences for millions of listeners.
What You'll Do
• Build and improve machine learning models that make Spotify Search more relevant, personalized, and engaging for listeners.
• Develop and optimize ranking and backend retrieval systems that help listeners discover music, videos, audiobooks, and other content.
• Explore emerging AI and agentic approaches to create more intuitive and conversational Search experiences.
• Design, implement, and evaluate machine learning solutions, taking ideas from early experimentation through production.
• Partner with engineers, product managers, designers, and researchers to identify opportunities and deliver meaningful improvements to Search.
• Use experimentation, data analysis, and performance metrics to understand model behavior, validate hypotheses, and improve the listener experience.
• Contribute to scalable machine learning infrastructure and engineering practices that support reliable, high-quality Search experiences.
• Share knowledge, challenge assumptions constructively, and help shape the technical direction of machine learning within the squad.
Who You Are
• You have experience building, deploying, and improving machine learning systems in production environments.
• You have a strong understanding of machine learning approaches for information retrieval, search ranking, recommendation systems, or personalization.
• You are proficient in Python and comfortable working with modern machine learning frameworks and data processing tools.
• You have experience and a desire to lean into backend engineering at Spotify scale.
• You understand how to design and evaluate experiments, interpret model performance, and translate technical findings into product improvements.
• You have experience working with large-scale datasets and understand the challenges of building reliable, scalable machine learning systems.
• You are curious about emerging AI technologies, including large language models and agentic systems, and interested in their potential to improve discovery experiences.
• You enjoy working across disciplines, communicating technical ideas clearly, and learning from different perspectives.
• You are comfortable navigating ambiguity, taking ownership of complex challenges, and balancing experimentation with practical delivery.
Where You'll Be
• This role is based in Eastern Standard Time
• We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
Compensation
Additional Information
The United States base range for this position is 184,049–262,928 USD, plus equity. The benefits available for this position include health insurance,
View original listing ↗