At a Glance
- Tasks: Design and build AI systems for personalised listening experiences at Spotify.
- Company: Join Spotify, the world's leading audio streaming service, in a dynamic team.
- Benefits: Flexible work options, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment focused on innovation and user-centric products.
- Why this job: Make a real impact on millions of listeners with cutting-edge AI technology.
- Qualifications: 5+ years in machine learning, strong Python skills, and experience with LLMs.
The predicted salary is between 80000 - 100000 € per year.
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, podcasts, and listeners better than anyone else and by leveraging the latest in Generative AI. Join us and you’ll give millions of listeners great music and talk experiences, personalized to each and every one of them.
The AI Foundation team within Personalization provides the state-of-the-art foundational data and tech with which we are inventing and shipping new interactive, personalized listening experiences. This is a team of about a hundred AI/ML Engineers, Applied Research Scientists, Product Managers, and domain experts.
You’ll join the Zeitgeist squad within the AI Foundation team. We focus on building the systems and models that help Spotify understand culture in real time—what’s trending, why it matters, and how it shapes listening. You’ll leverage large language models and agentic workflows, and work closely with engineers, data scientists, and product partners to turn signals into meaningful user experiences. This is an exciting mix of platform-level content understanding and experience-level user presentation.
What You’ll Do
- Design, build, and ship agentic systems that ground personalized listening experiences in cultural context and world knowledge, used by hundreds of millions of Spotify users.
- Develop and maintain pipelines for extracting, structuring, and serving cultural signals at scale, leveraging LLMs and agentic workflows.
- Partner closely with teams across Personalization to integrate foundational cultural data and tech into new agentic listening experiences.
- Own components end-to-end — from data pipelines and model training to production serving and monitoring.
- Design and build evaluation tooling (including LLM-as-judge frameworks and dataset analysis), and run experiments to evaluate the impact of cultural context signals on user experience and engagement.
- Help define the technical direction of the squad, contributing to architecture decisions, and shaping what building “0-to-1” experiences looks like in practice.
Who You Are
- You have 5+ years of experience building and shipping machine learning models end-to-end.
- You have a strong foundation in Python (Java and Scala are a plus) and experienced with GCP tools (e.g. Dataflow, BigQuery).
- You have hands‑on experience with LLMs and agent orchestration frameworks (e.g. LangChain, LlamaIndex, Pydantic), building tool‑calling agents, RAG, and vector databases.
- You have built and shipped production‑scale, data‑driven AI/ML systems, ideally in content understanding, knowledge graphs, NLP, MIR, or related domains.
- You are excited but not overhyped by the potential of Generative AI.
- You’re comfortable operating as a 0-to-1 builder — you thrive in ambiguous, exploratory spaces and can move from idea to experimentation to production with confidence.
- You care about building inclusive, user‑centric products, and you think about AI and ML in the context of products and user impact, not just tech.
- You have worked effectively in collaborative, cross‑functional environments.
- You care deeply about code quality, reliability, and scalability.
Where You’ll Be
This role is based in London or Stockholm. 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.
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Senior Machine Learning Engineer, Zeitgeist, Personalization in London employer: Spotify
At Spotify, we pride ourselves on being an exceptional employer, offering a vibrant work culture that champions inclusivity and innovation. As a Senior Machine Learning Engineer in our Personalization team, you'll have the opportunity to work with cutting-edge technology in a collaborative environment, while enjoying flexible working arrangements in either London or Stockholm. We are committed to your professional growth, providing ample opportunities to develop your skills and contribute to meaningful projects that enhance the listening experience for millions of users worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer, Zeitgeist, Personalization in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Spotify, especially those in the Personalization team. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your experience with LLMs and agentic workflows. This will not only impress but also demonstrate your hands-on expertise.
✨Tip Number 3
Ace the interview by being ready to discuss real-world applications of your work. Think about how you've used cultural signals in past projects and be prepared to share specific examples.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the Spotify family!
We think you need these skills to ace Senior Machine Learning Engineer, Zeitgeist, Personalization in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior Machine Learning Engineer role. Highlight your experience with LLMs and agent orchestration frameworks, as well as any relevant projects that showcase your skills in building data-driven AI/ML systems.
Showcase Your Passion:Let us see your excitement for Generative AI and how it can enhance user experiences. Share examples of how you've applied your knowledge in real-world scenarios, especially in content understanding or cultural context.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. Use clear language to describe your achievements and technical skills, making it easy for us to see why you’d be a great fit for our team.
Apply Through Our Website:We encourage you to submit your application directly through our website. This way, you’ll ensure it reaches the right people and you’ll have access to all the latest updates about the hiring process!
How to prepare for a job interview at Spotify
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals, especially around LLMs and agent orchestration frameworks. Be ready to discuss your past projects in detail, focusing on how you built and shipped models end-to-end.
✨Show Your Passion for Personalisation
Since the role is all about enhancing user experiences, think about how you can leverage cultural context in your work. Prepare examples of how you've used data to create personalised solutions in previous roles.
✨Collaborate Like a Pro
This position requires working closely with cross-functional teams. Be prepared to share experiences where you successfully collaborated with engineers, data scientists, or product managers. Highlight your communication skills and how you navigate team dynamics.
✨Think Big, Start Small
As a 0-to-1 builder, you’ll need to demonstrate your ability to take ideas from concept to production. Share examples of how you've tackled ambiguous projects, starting with small experiments that led to larger successes. This shows your innovative mindset and adaptability.