Why This Job is Featured on The SaaS Jobs
Within the SaaS ecosystem, personalization is a durable product lever because it directly shapes activation, retention, and long-term engagement. This role sits in a team explicitly focused on inventing new listening experiences using agentic systems and generative AI, which signals a product-led environment where machine learning is tightly coupled to what ships and how users interact with the platform.
For a SaaS career path, the standout value is end-to-end ownership of production ML, from prototyping through evaluation and rollout at meaningful scale. The remit spans interactive experiences, human feedback loops for LLM systems, and collaboration with product, design, research, and data science, all of which build transferable skill in turning model capability into measurable product behavior. The emphasis on best practices and community contribution also points to an engineering setting where system quality and repeatability matter.
This position tends to suit an engineer who prefers applied research translated into reliable software, and who is comfortable navigating ambiguity when new product surfaces are being defined. It also fits someone motivated by cross-functional iteration and by the discipline of testing, evaluation, and modular architecture in complex, user-facing ML systems.
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 Blend to Discover Weekly, we’re behind some of Spotify’s most-loved features. We built them by understanding the world of 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.
You’ll join the Horizon Product Area within the Sessions Studio, part of Spotify’s Personalization Mission. This team focuses on inventing and evolving new listening experiences powered by emerging technologies. From AI DJ to promptable playlists and generated podcasts, we’re exploring how agentic systems and generative AI can reshape how people interact with audio. You’ll work at the intersection of product innovation and cutting-edge machine learning to bring entirely new experiences to life for millions of listeners.
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What You'll Do
- Design, build, evaluate, and ship agentic based features and interactive experiences to bring our products to the next level
- 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 both inside the team as well as throughout the organization
- Actively contributed to a strong community of machine learning practitioners at Spotify
Who You Are
- 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 Americas 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 $184,050- $262,928 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
