Summer Internship, ML Engineering Intern | Personalization Mission (US)

New York, NY /
Students – Students /
Internship
/ Remote
Spotify has more than 400M listeners in more than 180 markets around the world, who use our music, podcast, and audiobook services to find what delights, entertains, educates, and informs them. Personalization provides the technology to serve them what they expect to find, to help them explore and find new things to enjoy, and for us to suggest things they might not be aware of that they would like. As a result, from Blend to Discover Weekly, the Personalization team is behind some of Spotify’s most-loved features. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.

We are looking for passionate Machine Learning Interns to join us on the Home Podcasts team and Mixer team.

Our mission on Home Podcasts is to build the best podcast listening lifecycle on Home that drives sustainable and strategic growth. You will investigate potential data sources that could contribute to our models and evaluate their usefulness. You will be able to improve upon both technical and business skills through industry experience that we hope to cater towards your career aspirations. Above all, your work will impact the way the world experiences podcasts.

The Mixer product area enables the core platform and ecosystem for Spotify's personalized music playlists. We build and improve a stack and models for multi-objective, multi-stakeholder recommendations in programmed playlists, serving millions of inference requests per second to help deliver the best personalized music sets to listeners. The project will be in the area of recommender systems and models, and will be defined to match the team needs and the candidate's experience at the time of the internship. Above all, your work will impact the way the world experiences music.

What you'll do

    • Apply machine learning, collaborative filtering, NLP, and deep learning methods to massive data sets
    • Prototype new algorithms, evaluate with small scale experiments, and later productionize solutions at scale to our users
    • Collaborate with a cross functional agile team of software engineers, data engineers, ML experts, and others to build new product features
    • Help drive optimization, testing and tooling to improve data quality
    • Iterate on recommendation quality through continuous A/B testing
    • Develop your technical (Python, Scala, SQL, Engineering fundamentals, etc) and soft skills
    • Participate in shadowing and mentoring opportunities with professionals

Who you are

    • You are interested in a career in Machine Learning
    • You are pursuing a Ph.D. or Master's degree in Machine Learning, Statistics or related field
    • You currently have valid work authorization to work in the country in which this role is based that will extend from June to August 2023
    • You have a strong mathematical background in statistics and machine learning
    • You have some experience with languages such as Python, Scala, SQL
    • You have strong written and communication skills
    • You are excited and eager to learn

Where you'll be

    • We are a distributed workforce enabling our band members to find a work mode that is best for them!
    • Where in the world? For this role, it can be within the AMER region in which we have a work location.
    • Prefer an office to work from instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
    • Working hours? We operate within the Eastern Standard time zone for collaboration.
Our paid summer internships last for 10-13 weeks and start at the beginning of June. The last day to apply is February 9th, 2023 at 10 AM CET.

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.