Why This Job is Featured on The SaaS Jobs
This role stands out in the SaaS landscape because it sits at the monetization-adjacent layer of a subscription platform: machine learning systems that decide which users see which strategic or paid promotions across core product surfaces. Rather than focusing solely on “what content is good,” the remit is about targeting, measurement, and real-time decisioning—capabilities that many SaaS businesses rely on as they mature their growth and lifecycle tooling.
From a long-term SaaS career perspective, the scope is unusually end-to-end: owning the ML stack, influencing backend architecture, and tying model performance to campaign-level outcomes. That combination builds durable experience in operating ML as a product capability—defining success metrics with product partners, managing trade-offs between relevance, reliability, and cost, and delivering systems that need to perform at very large scale.
The position is best suited to an engineering leader who prefers cross-functional problem framing over purely research-oriented work, and who enjoys coaching teams through ambiguous, high-stakes platform decisions. It will appeal to managers who want their leadership impact to be visible through measurable product interventions, while still staying close to infrastructure and distributed-systems realities.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. From Daily Mix to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of audiobooks, 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.
This team is the machine learning team within the PZN Strategic Programming (PSP) Product Area, responsible for powering all targeting of strategic and paid promotions across Spotify’s major surfaces—including Home, Browse, and Search. We build the ML infrastructure and models that determine which users should see which content—be it music, podcasts, audiobooks, or video—so that every intervention delivers value to listeners and impact for creators.
Team owns the entire ML stack for targeting, including real-time decisioning and campaign-level optimization. We work at the intersection of machine learning, backend engineering, and large-scale distributed systems—ensuring that Spotify’s strategic programming is personalized, scalable, and measurable.
We are now looking for a Machine Learning Engineering Manager to lead this impactful team. In this role, you’ll guide ML, backend and data engineers working on mission-critical systems that sit at the heart of Spotify’s content promotion strategy. You'll shape how we evolve our targeting capabilities to support diverse content formats, deliver engaging experiences to users, and drive measurable outcomes for artists, publishers, and partners.
In this role, you will lead a team of Engineers all based in Europe, and will collaborate with a product manager and other partners to define and shape product roadmap and technical strategy. You will also be responsible for the individual growth and organizational health of your team.
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What You'll Do- Manage a team building recommendation systems for 500M+ monthly Spotify customers.
- Collaborate with product, design and insights partners to create a roadmap, define success metrics and deliver products.
- Influence the technical design and architecture of our stack. Support your team in developing scalable and reliable systems.
- Manage stakeholders such as Music, Audiobook and Podcast mission.
- Lead other efforts that fit your passion and Spotify’s needs..
Who You Are- You understand the value of a diverse workforce. You have a demonstrated track record of moving tech orgs closer to representing the world we live in; you build teams with these values.
- You have strong mentorship and coaching skills, and thrive when helping individuals and teams perform to their full potential.
- You have demonstrated the ability to deliver high quality, reliable, and cost-efficient recommendation systems for large scale (100M+) consumer applications.
- You are able to distill complex information into easy-to-understand concepts, and understand how to lead a team through ambiguity.
- You stay up-to-date with the state-of-the-art technology in machine learning.
- You have managed teams and individuals for a minimum of 2 years.
Where You'll Be- We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location.
- Excluding France for now due to on-call restrictions.
- This team operates within the Central Eastern time zone for collaboration.
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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.
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.
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.