Machine Learning Engineer - Subscriptions
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- Work arrangement
- hybrid
- Employment
- Permanent
- Stated compensation
- Not specified
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Checked for applicants in Qatar; employer sponsorship is not needed. Based on the source posting · not a hiring or work-authorization guarantee.
Office attendance is required. Relocation and work permission have not been assessed.
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- The stated geographic scope includes your country.
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- Office attendance is required. Relocation and work permission have not been assessed.
- Visa sponsorship is not specified.
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Requirements
3 with evidence6 unclear or unstated- Remote policy
- hybrid
“Provider workplace type: hybrid”
From employer posting metadata - Geographic scope
- EMEA
“For this role, you can be within the EMEA region as long as we have a work location”
See matched passage in original description ↓ - Timezone / hours
- This team operates within the Central European and GMT time zone for collaboration.
“This team operates within the Central European and GMT time zone for collaboration.”
See matched passage in original description ↓ - Employment type
- Permanent
7 fields not stated in this posting
- Employer sponsorship
- Not specified
- Degree requirement
- Not specified
- Security clearance
- Not mentioned
- Citizenship requirement
- Not mentioned
- Minimum experience (years)
- Not specified
- Work authorization
- Not specified
- Compensation
- Not specified
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Original job description
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At Spotify, our Subscriptions Mission focuses on creating experiences that help listeners discover the value of Spotify, become subscribers, and stay with us for the long term. By combining technology, experimentation, and a deep understanding of our users, we help connect artists and fans while building a sustainable subscription business.
Within the Subscriptions Mission, the Subs Foundational Models Product Area is part of the Subs User Understanding Studio. We build scalable machine learning solutions that personalize the subscriber journey, from conversion through to long-term retention. Working closely with teams across the mission, we develop ML solutions that improve key business metrics, including subscriber growth, monthly active users, and Premium retention.
We're looking for a Machine Learning Engineer to join our Radius squad. You'll take ownership of impactful ML initiatives, develop and improve production models, and contribute to the foundational ML capabilities that power personalization and optimization across Subscriptions.
Your work could include reducing friction for Free users while balancing retention and conversion, improving payment experiences to reduce Premium churn, or developing reusable models such as subscriber embeddings that support multiple products and use cases.
What You'll Do
Who You Are
Where You'll Be
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We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location
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This team operates within the Central European and GMT time zone for collaboration.
Matched by role category. Review each posting’s requirements before applying.
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