Spotify

Tech / AI / Software

MachineLearningEngineer-Subscriptions

New York, New York, United States; boston, massachusetts, united states Permanent Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“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.

Tech / AI / Software

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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