At a Glance
- Tasks: Design and build AI systems for personalised listening experiences at Spotify.
- Company: Join Spotify's innovative Personalization team, shaping music experiences for millions.
- Benefits: Flexible work options, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment focused on inclusivity and user-centric product development.
- Why this job: Make a real impact on how people enjoy music and podcasts with cutting-edge AI.
- 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 in London employer: Creandum Advisor LLP
Spotify is an exceptional employer that fosters a culture of innovation and inclusivity, making it an ideal place for a Senior Machine Learning Engineer to thrive. With a focus on personal growth and collaboration, employees are encouraged to explore their creativity while working on cutting-edge technology that impacts millions of listeners worldwide. The flexibility to work from either London or Stockholm, combined with a commitment to diversity and accessibility, ensures that every team member feels valued and empowered to contribute to the future of music and podcasts.
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 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
Practice makes perfect! Get ready for technical interviews by brushing up on your Python and GCP tools. Mock interviews with friends or using online platforms can help you feel more confident.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Spotify family. Don’t miss out!
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 enthusiasm 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 technical skills and experiences, making it easy for us to see how you fit into the Zeitgeist squad.
Apply Through Our Website:We encourage you to submit your application 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 role and our team!
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 team success.
✨Think User-Centric
Spotify values inclusivity and user-centric products, so come ready to discuss how your work impacts users. Think about how cultural context can enhance listening experiences and be prepared to share your thoughts on building products that resonate with diverse audiences.
✨Be Ready for Problem-Solving
Expect some technical questions or case studies during the interview. Prepare to demonstrate your problem-solving skills by walking through how you would approach building a new feature or improving an existing one. Show them you can think critically and creatively in ambiguous situations!