At a Glance
- Tasks: Design and build AI systems for personalised music experiences enjoyed by millions.
- Company: Join Spotify's innovative Personalization team, shaping the future of listening.
- Benefits: Flexible work options, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment focused on inclusivity and user-centric products.
- Why this job: Make a real impact on how people experience music and podcasts.
- Qualifications: 5+ years in machine learning, strong Python skills, and experience with LLMs.
The predicted salary is between 70000 - 90000 € 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.
Senior Machine Learning Engineer, Zeitgeist, Personalization employer: Creandum Advisor LLP
At Spotify, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our Personalization team, based in vibrant London or Stockholm, provides employees with the flexibility to work where they thrive best while contributing to groundbreaking projects that enhance user experiences for millions. With a strong emphasis on inclusivity, professional growth opportunities, and a commitment to leveraging cutting-edge technology, we empower our team members to make a meaningful impact in the world of music and podcasts.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer, Zeitgeist, Personalization
✨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 might just get your foot in the door.
✨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 demonstrate your expertise but also your passion for the role.
✨Tip Number 3
Ace the interview by being ready to discuss real-world applications of your work. Think about how your past projects have impacted user experiences and be prepared to share those stories.
✨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
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 user-centric products.
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 the team.
Apply Through Our Website:We encourage you to submit your application through our website. This way, you’ll ensure that your application reaches the right people and gets the attention it deserves. Plus, it’s super easy to do!
How to prepare for a job interview at Creandum Advisor LLP
✨Know Your Stuff
Make sure you brush up on your machine learning models and the latest in Generative AI. Be ready to discuss your past projects, especially those involving LLMs and agent orchestration frameworks. This is your chance to show how your experience aligns with what the Personalization team is doing!
✨Show Your Collaborative Spirit
Since this role involves working closely with engineers, data scientists, and product partners, be prepared to share examples of how you've successfully collaborated in cross-functional teams. Highlight your ability to communicate complex ideas clearly and how you’ve contributed to inclusive, user-centric products.
✨Think Like a Builder
They’re looking for someone who thrives in ambiguous spaces and can take ideas from concept to production. Prepare to discuss how you've approached building systems from scratch, including any challenges you faced and how you overcame them. This will demonstrate your 0-to-1 building mindset.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, the cultural context they’re focusing on, and how they measure user engagement. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.