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. We ask that our team members be physically located in Central European time or Eastern Standard/Daylight time zones for the purposes of our collaboration hours.
Spotify has more than 500M listeners in more than 180 markets worldwide, 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.
We are looking for a Staff Machine Learning Engineer to help us define and build the next generation of Spotify features and products. You will be responsible for the design and development of large language models that will power the personalization engine of Spotify to provide a better user experience and surface the content to individual users that maximizes their long-term satisfaction.
At Spotify we say "Listening is everything". In addition to our market lead in music streaming, we have broadened our offering to include podcasts and audiobooks. We invest deeply in making sense of this new content to power our personalization and recommendation systems. You will be part of an interdisciplinary team focusing on building robust systems with large language models at their core that can be used downstream to power search, discovery, and recommendations across the platform.
What You'll Do
- Contribute to the technical design, architecture, development, and evaluation of a Foundational large language model to apply Transformer/LLM technology to the next generation of Spotify features and products
- Provide technical leadership and be an active contributor to the Spotify group of machine learning practitioners that are building LLMs and their associated infrastructure
- Collaborate with a multi-functional, agile team, spanning research science, design, data science, product management, and engineering to build new product features that advance our mission to connect artists and fans in personalized and relevant ways
Who You Are
- You have hands-on experience building and implementing large language models using tools at scale, such as PyTorch, TensorFlow, Ray, Python, Java, and Scala
- You have a strong track record taking new research ideas in Machine Learning, Natural Language Processing into production
- You have in-depth, working knowledge of Transformers and LLMs for content understanding tasks
- You have experience with model training, deployment, and serving using Google Cloud Platform and the associated tools and technologies
- You have contributed code and models to large-scale (100M+) consumer applications that are both reliable and cost-efficient
- You understand the architecture and development workflow for large-scale batch and streaming machine-learning systems
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 Americas region in which we have a work location.
- Prefer an office to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
The United States base range for this position is USD 202,353- 289,076, 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.
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.