[Hiring] Machine Learning Engineer - Personalization @Spotify

Role Description

The Personalization (PZN) team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts and audiobooks better than anyone else so that we can make great recommendations to every individual and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like Home and Search as well as original playlists such as Made For You, Discover Weekly and Daily Mix.

Our team’s mission is to bring emerging search and agentic experiences to a mature state: exploring, defining, building, validating and optimizing new ideas. These can include new content types in our Search engine or emerging user interaction patterns.

What You'll Do

• Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
• Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
• Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.

Qualifications

• You have a background in machine learning, enjoy applying theory to develop real-world applications, with experience in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
• You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
• You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
• You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS.
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation.

Requirements

• Flexibility to work where you work best within the North America region.
• This team operates within the Eastern Standard time zone for collaboration.

Benefits

• United States base range for this position is $170,000 - $212,000 plus equity.
• 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.

Company Description

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.

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!

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.