Senior Machine Learning Engineer, Personalization

Spotify AB; New York (NY); Hybrid; USD 176,000 - 252,000; Full time

Job summary

Spotify’s Safe-and-Sound team is seeking an experienced ML engineer to design and implement machine learning solutions enhancing user personalization. Candidates should excel in tackling complex real-world problems, collaborating across teams, and be adept in various programming languages and ML frameworks.

Benefits

Extensive learning opportunities

Flexible share incentives

Global parental leave

Employee assistance program

Flexible public holidays

Qualifications

• Experienced ML practitioner with hands-on expertise in production ML systems.
• Strong background in machine learning and natural language processing.
• Experience with end-to-end tech specs in collaboration with product teams.

Responsibilities

• Design and implement ML solutions for Spotify's personalization products.
• Collaborate with teams to develop features that connect artists and fans.
• Prototype and scale solutions for millions of users.

Skills

Machine Learning

Natural Language Processing

Generative AI

End-to-End ML Systems

Distributed Data Processing

Tools

Java

Scala

Python

Pytorch

TensorFlow

Scikit-learn

Apache Beam

Apache Spark

GCP

AWS

Job description

The Safe-and-Sound team makes Spotify safe and enjoyable for every listener. From podcast recommendations to AI Playlists, we’re a part of some of Spotify’s most-loved features. We build Responsible AI solutions by understanding our music, podcasts and users better than anyone else. Join us and you’ll keep millions of users listening by making recommendations safe for each and every one of them.

Location

• New York

Job type

Permanent

What You'll Do

• Design, build, evaluate, and ship ML solutions for safety in Spotify’s personalization products
• Collaborate with cross-functional teams spanning user research, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and useful ways
• Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
• Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
• Be part of an active group of machine learning practitioners in New York (and across Spotify), collaborating with one another

Who You Are

• An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment
• Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications
• Hands-on expertise with implementing end-to-end production ML systems at scale in Java, Scala, Python, or similar languages. Experience with Pytorch, TensorFlow, Scikit-learn is a strong plus
• Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams
• Experience with large-scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS

Where You'll Be

• This role is based in New York
• 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

Extensive learning opportunities, through our dedicated team, GreenHouse.

Flexible share incentives letting you choose how you share in our success.

Global parental leave, six months off - for all new parents.

All The Feels, our employee assistance program and self-care hub.

Flexible public holidays, swap days off according to your values and beliefs.

Learn about life at Spotify

The United States base range for this position is$176,166- $251,666 plus equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave. These ranges may be modified in the future.