The Music Mission team owns Spotify’s end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale.
The DISCO Product Area is focused on building promotional tools that help artists reach more fans. Our products serve artists at scale through Spotify for Artists, and we’re building on the momentum of Discovery Mode to help artists and their teams find new listeners when it matters most. As a Staff Machine Learning Engineer, you’ll help shape the Machine Learning technical strategy for this high-impact area, partnering across engineering, product, data science, research, and design to create tools that help artists grow their audiences while supporting Spotify’s core business.
What You'll Do
- Help define and drive the Machine Learning engineering strategy for Discovery Mode and related royalty programs, translating product goals into scalable technical solutions.
- Design, build, evaluate, ship, and refine production Machine Learning systems through hands-on development.
- Provide technical leadership across complex ML initiatives, helping teams make thoughtful architectural and engineering decisions while balancing near- and long-term priorities.
- Collaborate with user research, design, data science, product management, and engineering to build new product capabilities that strengthen connections between artists and fans.
- Prototype new approaches and turn successful ideas into reliable, scalable solutions for Spotify for Artists customers.
- Drive experimentation, optimization, testing, and tooling that improve the quality, reliability, and effectiveness of our Machine Learning systems.
- Partner with engineers and Machine Learning practitioners across Spotify, including Music Tech Research and Personalization, to explore and develop new approaches to music promotion.
- Help grow the technical capabilities of the broader engineering community through mentorship, knowledge sharing, and strong engineering practices.
Who You Are
- You have deep experience with Machine Learning and a strong understanding of Machine Learning algorithms, modeling approaches, evaluation, and experimentation.
- You have hands-on experience designing and implementing production Machine Learning systems at scale using languages such as Python, Java, Scala, or similar.
- You can set technical direction for complex ML problems while remaining close to implementation and delivery.
- You care about reliable software, data-informed development, disciplined experimentation, and building systems that perform effectively at scale.
- You enjoy leading technically complex projects from idea through production and working closely with teammates and partners to deliver meaningful outcomes.
- You are comfortable navigating ambiguity, evaluating trade-offs, and creating clarity on high-impact initiatives.
- You communicate technical decisions and risks clearly and can build alignment with senior technical leaders and cross-functional partners.
- You care about creating products that better serve artists and their teams, and you take a collaborative, team-first approach to helping others do their best work.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
- This team operates within the Eastern time zone for collaboration.
The United States base range for this position is $227,495.00 - $324,993 USD, 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, paid flexible holidays, and 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.
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.
Skills Required
- Deep experience with machine learning, including algorithms, modeling approaches, evaluation, and experimentation
- Hands-on experience designing and implementing production machine learning systems at scale
- Experience using languages such as Python, Java, Scala, or similar
- Ability to set technical direction for complex machine learning problems while remaining involved in implementation and delivery
- Experience leading technically complex projects from ideation through production
- Ability to navigate ambiguity, evaluate trade-offs, and create clarity on high-impact initiatives
- Ability to communicate technical decisions and risks clearly and build alignment with senior technical leaders and cross-functional partners
- Commitment to reliable software, data-informed development, disciplined experimentation, and scalable systems
- Collaborative, team-first approach and interest in building products for artists and their teams
Spotify Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Spotify and has not been reviewed or approved by Spotify.
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Flexible Benefits — Employees consistently praise the total compensation package beyond base salary, highlighting a mix of RSUs, cash incentives, and stipends alongside core pay. The package is described as flexible and customizable through equity choices (e.g., RSUs, options, cash) that can be tailored for long-term wealth building.
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Leave & Time Off Breadth — Time-off offerings are repeatedly highlighted as substantial, including generous vacation, paid sick days, volunteer time, and flexible holidays. These policies are framed as a meaningful part of the overall rewards experience beyond salary.
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Healthcare Strength — Health coverage is portrayed as comprehensive, spanning medical, dental, vision, life insurance, disability coverage, and mental health support. Additional employer contributions to HSAs are cited as strengthening the overall health and wellness value proposition.
Spotify Insights
What We Do
Spotify transformed music listening forever when it launched in Sweden in 2008. Discover, manage and share over 50m tracks for free, or upgrade to Spotify Premium to access exclusive features including offline mode, improved sound quality, and an ad-free music listening experience.
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