- Be part of a machine learning team specializing in personalization and discovery on Spotify, and in the process push innovation and chip in to the wider research community by publishing papers.
- Apply your machine learning knowledge to problems in search and recommendation, information extraction, knowledge representation, natural language processing, human-computer interaction, and more broadly machine learning, combining insights from your expertise with those of our diverse team.
- Be a valued member of an autonomous, multi-functional team working in collaboration with other scientists, engineers, product managers, designers, user researchers, and analysts across Spotify to craft creative solutions to challenging problems.
- Work on a broad range of Spotify features such as personalised playlists (Discover Weekly and Daily Mix), the Homepage, Search, and other ML systems powering recommendations to millions of users with billions of interactions.
- You are pursuing a Ph.D. in Machine Learning, Statistics, or related areas.
- You have publications in communities such as NeurIPS, ICML, ICLR, AISTATS, UAI, AAAI, WWW, SIGIR, WSDM, RecSys, KDD or related venues.
- You have strong programming skills using the following languages/libraries: Python, Numpy, TensorFlow, PyTorch.
- You have experience in one or more of the following fields: Reinforcement Learning / Multi-armed Bandits, Graph Learning, Representation Learning, and Probabilistic Machine Learning.
- You are able to communicate your ideas and enjoy collaboration.
- 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 EMEA region in which we have a work location.
- For this role, you can choose to either work from home or from one of our office locations.
- Working hours? We operate within the Central European and GMT time zones time zone for collaboration.
Company
Location
London, England - United Kingdom
Job type
Full-Time
Python Job Details
Students
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of music and podcasts better than anyone else. Join us and you’ll keep millions of users listening by making great recommendations to each and every one of them.
Location
London or Remote EMEA
Job type
Internship
We are looking for an intern to join our team of research scientists. You will develop and evaluate machine learning methods, demonstrate standard processes in powering the next generation of machine learning research, and make sure that every user interaction with Spotify is outstanding through personalization and discovery.
What You'll Do
Who You Are
Where You'll Be
Our global benefits
Extensive learning opportunities, through our dedicated team, GreenHouse.
All The Feels, our employee assistance program and self-care hub.
Social events, everything from fikas and team outings to concerts, panels and talks.
Flexible public holidays, swap days off according to your values and beliefs.
Spotify Premium Account, listen without limits with a free employee account.
Swag, a Spotify welcome kit and official merch you can’t get anywhere else.
Learn about life at Spotify
Our paid summer internships last for 10-13 weeks and start at the beginning of June.
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.
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