Why This Job is Featured on The SaaS Jobs
This Machine Learning Engineer, Personalization role stands out because it sits at the heart of a subscription software product where retention and engagement are shaped by algorithmic decisions. The remit spans building and refining ML systems that influence what users see, while also incorporating “Responsible AI” considerations—an increasingly central theme for SaaS platforms operating at large scale and under evolving trust and safety expectations.
From a SaaS career perspective, the work maps closely to durable patterns: productionizing models, running disciplined experimentation, and iterating based on measurable product impact. Collaboration across research, design, product, data science, and engineering reflects how mature SaaS organizations ship ML as a product capability rather than a research output. Experience gained here—evaluation frameworks, testing, tooling, and reliability—translates well to other SaaS domains where personalization and ranking drive outcomes.
The role is best suited to practitioners who enjoy end-to-end ownership, from prototyping through deployment and ongoing optimization. It will fit someone motivated by applied ML in real user-facing systems, comfortable partnering across functions, and interested in building approaches that balance relevance with safety constraints in a large-scale SaaS environment.
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 Safe-and-Sound team makes Spotify safe and enjoyable for every listener. From podcast recommendations to AI Playlists, we’re a part of some of Spotify’s most-loved features. We build Responsible AI solutions by understanding our music, podcasts and users better than anyone else. Join us and you’ll keep millions of users listening by making recommendations safe for each and every one of them.
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What You'll Do- Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
- Collaborate with a cross 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 new approaches and production-ize solutions at scale for our hundreds of millions of active users
- Help drive optimization, testing, and tooling to improve quality
- Be part of an active group of machine learning practitioners in New York (and across Spotify) collaborating with one another
Who You Are- You have a strong background in machine learning, with experience and expertise in personalized machine learning algorithms, especially recommender systems.
- You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages. Experience with XGBoost, TensorFlow is also a plus.
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
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 Standard time zone for collaboration.
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The United States base range for this position is $136,878- $195,540 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, 13 paid flexible holidays, 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.
