Senior Machine Learning Engineer, Zeitgeist, Personalization

Senior Machine Learning Engineer, Zeitgeist, Personalization

Full-Time 70000 - 90000 € / year (est.) Home office (partial)
Spotify

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, known for innovation.
  • Benefits: Flexible work options, inclusive culture, and opportunities for personal growth.
  • Other info: Collaborative environment with a focus on inclusivity and user-centric products.
  • Why this job: Make a real impact on millions of listeners with cutting-edge technology.
  • 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.

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 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 worldwide.

Spotify

Contact Detail:

Spotify Recruiting Team

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 even lead to 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 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 you've used machine learning to solve problems 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

Machine Learning
Python
GCP Tools
Dataflow
BigQuery
Large Language Models (LLMs)
Agent Orchestration Frameworks

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, Python, and any relevant projects that showcase your skills in building data-driven AI systems.

Show Your Passion for Personalisation:Let us know why you’re excited about personalisation in audio experiences! Share any personal projects or insights related to music, podcasts, or user-centric design that demonstrate your enthusiasm for the field.

Be Clear and Concise:When writing your application, keep it straightforward. Use clear language to describe your experience and achievements, making it easy for us to see how you fit into the Zeitgeist squad.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!

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.

Cultural Context is Key

Since the role involves understanding cultural signals, think about how you can leverage your knowledge of trends and user behaviour in your answers. Prepare examples of how you've integrated cultural context into your previous work.

Collaboration is Crucial

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 foster teamwork.

Show Your Passion for AI

Express your excitement about Generative AI and its potential impact on user experiences. Share your thoughts on the future of AI in personalisation and how you envision contributing to innovative solutions at Spotify.