Spotify
Tech / AI / Software
MachineLearningEngineer-Subscriptions
Neural analysis suggests this role is
optimal for Mid candidates.
“Machine Learning Engineer - Subscriptions at Spotify. Skills: machine learning, production ML systems, data pipelines, cloud platforms. Contribute to designing, building, evaluating, and improving machine learning models that power personalization across the subscription funnel. Prototype new machine learning approaches and scale them to production for hundreds of millions of users”
What You'll Achieve.
ship impactful features; improve model quality and reliability; driving measurable business impact
Industry & Context.
What They're Looking For.
Must Have
3+ years of experience applying machine learning in production environments, Hands-on experience building and maintaining production ML systems using Python, Scala, or similar languages, Experience working with modern ML frameworks such as PyTorch or distributed systems like Ray, Experienced in building data pipelines and independently sourcing and preparing data for modeling, Worked with cloud platforms such as GCP or AWS
Nice to Have
PhD preferred, specific ML framework experience, cloud platform certs
What You'll Do.
Contribute to designing
and improving machine learning models that power personalization across the subscription funnel
Prototype new machine learning approaches and scale them to production for hundreds of millions of users
Help optimize experimentation frameworks
and tooling to improve model quality and reliability
Build and maintain robust data pipelines and production-ready ML systems
Contribute to improving how we personalize messaging
and user journeys across discovery and conversion surfaces
How You'll Work.
Team & Collaboration
Work closely with a cross-functional team of engineers, data scientists, product managers, designers, and researchers to ship impactful features; Participate in knowledge sharing within the machine learning community across Spotify; enjoy working in collaborative, cross-functional teams and contributing to shared outcomes
Communication Scope
comfortable explaining machine learning concepts, assumptions, and trade-offs to both technical and non-technical partners
Full Job Description
## What You'll Do Contribute to designing, building, evaluating, and improving machine learning models that power personalization across the subscription funnel Work closely with a cross-functional team of engineers, data scientists, product managers, designers, and researchers to ship impactful features Prototype new machine learning approaches and scale them to production for hundreds of millions of users Help optimize experimentation frameworks, testing strategies, and tooling to improve model quality and reliability Build and maintain robust data pipelines and production-ready ML systems Participate in knowledge sharing within the machine learning community across Spotify Contribute to improving how we personalize messaging, offers, and user journeys across discovery and conversion surfaces ## Who You Are You have 3+ years of experience applying machine learning in production environments You are comfortable explaining machine learning concepts, assumptions, and trade-offs to both technical and non-technical partners You have hands-on experience building and maintaining production ML systems using Python, Scala, or similar languages You have experience working with modern ML frameworks such as PyTorch or distributed systems like Ray You are experienced in building data pipelines and independently sourcing and preparing data for modeling You have worked with cloud platforms such as GCP or AWS You care about experimentation, iteration, and using data to guide decisions You enjoy working in collaborative, cross-functional teams and contributing to shared outcomes You are motivated by driving measurable business impact through your work ## Where You'll Be This role is based in New York or Boston 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. ## Additional Information Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter wher
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