Why This Job is Featured on The SaaS Jobs
This Senior Machine Learning Engineer role sits at a mature, product-led subscription platform where personalization is a core retention lever. Within the SaaS ecosystem, it highlights how large-scale consumer subscriptions increasingly rely on applied ML and LLM-driven interfaces to shape discovery, reduce friction, and deepen engagement across repeated sessions.
For a SaaS career, the standout value is end-to-end ownership of systems that must perform reliably in production, not just in notebooks. Work spanning intent understanding, multi-turn context, and agentic workflows builds durable skills in shipping AI features with measurable quality, latency constraints, and operational feedback loops. The emphasis on evaluation frameworks also aligns with a broader industry shift toward disciplined measurement of LLM behavior, a capability that transfers across SaaS product areas where trust and consistency matter.
The role fits an engineer who prefers pairing experimentation with engineering rigor and who is motivated by cross-functional delivery into user-facing surfaces. It is well suited to someone comfortable navigating ambiguity in model behavior, iterating against real usage signals, and treating reliability as a first-class product requirement in subscription software.
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.
The Personalization team at Spotify makes deciding what to listen to next feel effortless for hundreds of millions of users — from Discover Weekly to our newest AI-powered experiences. We’re now building conversational AI capabilities that let users interact with Spotify in natural language. You’ll join a squad working at the core of this space, shaping how users discover and engage with audio through intelligent, responsive systems.
\n
What You'll Do
- Design and ship production-grade machine learning systems powering conversational and agentic AI experiences
- Build systems that interpret user intent, manage context across multi-turn interactions, and handle ambiguity reliably at scale
- Develop and evolve agentic workflows including memory, context management, and multi-step tool orchestration
- Create evaluation frameworks, including LLM-as-judge pipelines, to measure quality and guide iteration
- Partner closely with product, engineering, and design to deliver seamless, user-facing experiences
- Balance experimentation with production rigor, ensuring performance, latency, and reliability at Spotify scale
- Continuously improve agent behavior through tight feedback loops between evaluation and real-world usage
Who You Are
- You have 5+ years of experience building and shipping machine learning systems in production environments
- You are experienced with large language models and have worked on real-world applications beyond experimentation; shipped and maintained large scale systems with LLMs
- You have a deep understanding of challenges in conversational or agentic systems, such as context handling and multi-step reasoning
- You know how to evaluate ML systems rigorously and have experience designing metrics or evaluation pipelines
- You are comfortable debugging complex interactions between models, tools, and system constraints like latency
- You care about building reliable, scalable systems that deliver high-quality user experiences
- You enjoy working cross-functionally and contributing to a collaborative, inclusive team environment
Where You'll Be
- This role is based in New York
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home
\n
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.
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.
