Why This Job is Featured on The SaaS Jobs
This Machine Learning Engineer role sits at a particularly relevant intersection in SaaS: subscription consumer software operating at massive scale and increasingly shaped by generative AI. The focus on contextual “storytelling” powered by LLMs reflects a broader shift in SaaS product strategy—moving beyond recommendations toward richer, personalized product surfaces that are continuously updated through data and model iteration.
From a career perspective, the work maps closely to durable SaaS competencies: taking ML prototypes into production, measuring real user impact, and operating systems that must be reliable for a large active user base. The remit spans evaluation, testing discipline, and cross-functional delivery with product, design, and research—experience that translates well across SaaS teams building personalization, search, discovery, and AI-assisted UX.
This position is best suited to an ML engineer who prefers end-to-end ownership over isolated modeling work, and who is motivated by applied NLP and LLM system design rather than purely academic experimentation. It also fits someone comfortable collaborating across functions and contributing to shared engineering practices in an established organization with a mature ML community.
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 (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.
The Context team’s mission is to own and innovate on contextual story telling to enhance the listening experience. Using a mixture of human written content and LLMs, we strive to provide depth and connection for all listeners. We are looking for a Machine Learning Engineer to join our team to build and improve our storytelling capabilities.
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What You'll Do- Design, build, evaluate, and ship LLM based solutions that tell stories about our content and our users
- Collaborate with cross functional teams 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 useful ways
- Prototype new approaches and productionize solutions at scale for our hundreds of millions of active users
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
- Be part of an active group of machine learning practitioners
Who You Are- An experienced ML practitioner motivated to work on complex real-world problems in a fast-paced and collaborative environment -
- Strong background in machine learning, natural language processing, and generative AI, with experience in applying theory to develop real-world applications
- Hands-on expertise with implementing end-to-end production ML systems at scale. Experience with production LLM scale based systems is a plus
- Experience with incorporating human feedback to improve LLM based systems using technicals like DPO, KTO, and reinforcement fine-tuning
- Experience with designing end-to-end tech specs and modular architectures for ML frameworks in complex problem spaces in collaboration with product teams
- Experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, and cloud platforms like GCP or AWS
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 $138,250- $197,500 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.
