Machine Learning Engineering Manager
hace 6 días
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. 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..
- 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.
- 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.
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. 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.
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