Senior Machine Learning Engineer, Reinforcement Learning, Personalization

New York, NY

Applications have closed
Spotify logo

Spotify

We grow and develop and make wonderful things happen together every day. It doesn't matter who you are, where you come from, what you look like, or what music you love. Join the band!

View all employer listings

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.
We are looking for a Senior Machine Learning Engineer to join our team to help us advance the development and application of reinforcement learning techniques to recommender systems. You will be working with a multi-disciplinary team who’s driving the application of novel methods at scale to make Spotify’s beloved personalized playlists even better. As a senior engineer in the team, you will influence the direction within the team but also work with multiple partners to power different personalization projects across Spotify. This is an outstanding opportunity to redefine audio recommendation with reinforcement learning based approaches to reshape Spotify’s existing products and develop new ones.Join us and you’ll keep millions of users listening to outstanding recommendations every day. We’re a team of technologists, product insight specialists, designers, and product managers across the United States and Europe.

What You'll Do

  • Contribute in crafting, building, evaluating, shipping, and refining Spotify’s personalization products by hands-on ML development
  • Collaborate with a multi-functional agile team 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 relevant ways
  • Prototype innovative approaches and productionize solutions at scale for our hundreds of millions of active users
  • Promote and role-model standard processes of ML model development, testing, evaluation, etc, both inside the team as well as throughout the organization.
  • Be part of an active group of machine learning practitioners across Spotify

Who You Are

  • You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with experience and expertise in personalized machine learning algorithms, especially recommender systems
  • You have experience of feature engineering and prototyping machine learning applications, that have been deployed to production
  • You have hands-on experience implementing production machine learning systems at scale in Python, Scala, Java or similar languages. Previous shown experience with frameworks such as Tensorflow and the Tensorflow ecosystem (TFX) is also a plus.
  • You have experience with data pipeline tools like Apache Beam, Scio, etc., and cloud platforms like GCP or AWS.
  • You appreciate agile software processes, data-driven development, reliability, and responsible experimentation.
  • You routinely survey research publications in the machine learning and software engineering communities.
  • You love your customers even more than your code

Where You'll Be

  • We are a distributed workforce enabling our band members to find a work mode 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.
  • Working hours? We operate within the Eastern Standard time zone for collaboration.
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.
Global COVID and Vaccination DisclosureSpotify is committed to safety and well-being of our employees, vendors and clients. We are following regional guidelines mandating vaccination and testing requirements, including those requiring vaccinations and testing for in-person roles and event attendance. For the US, we have mandated that all employees and contractors be fully vaccinated in order to work in our offices and externally with any third-parties. For all other locations, we strongly encourage our employees to get vaccinated and also follow local COVID and safety protocols.

* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net

Tags: Agile AWS Engineering Feature engineering GCP Machine Learning Python Recommender systems Research Scala Streaming TensorFlow Testing

Region: North America
Country: United States
Job stats:  27  7  0

Other jobs like this

Explore more AI/ML/Data Science career opportunities

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.