Senior Machine Learning Engineer, Personalization
Senior ML Engineer on Spotify's Personalization team (Growlithe squad) building and improving machine learning models for Search — ranking, backend retrieval, and personalized discovery — while exploring LLM/agentic search experiences. Core stack: Python, modern ML frameworks, large-scale data processing, and experimentation.
- Compensation
- $184K–$262.9K / yr
- Location
- New York, NY
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Experience building, deploying, and improving machine learning systems in production environments
- Strong understanding of ML approaches for information retrieval, search ranking, recommendation systems, or personalization
- Proficient in Python and comfortable with modern ML frameworks and data processing tools
- Experience and desire to lean into backend engineering at Spotify scale
- Ability to design and evaluate experiments, interpret model performance, and translate findings into product improvements
- Experience working with large-scale datasets and building reliable, scalable ML systems
- Curiosity about emerging AI technologies, including large language models and agentic systems
- Cross-disciplinary collaboration and clear communication of technical ideas
- Comfort with ambiguity, ownership of complex challenges, and balancing experimentation with practical delivery
Full 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.
Growlithe is a fast-moving squad within Spotify's Conversation Product Area, focused on bringing emerging Search and agentic experiences to life. We explore, define, build, validate, and optimize new ideas to help listeners discover the content they love. Our work spans personalized Search, music video discovery and ranking, audiobook Search expansion, and the foundations of more social Search experiences.
We're looking for a Senior Machine Learning Engineer to help shape the next generation of Search at Spotify. You'll work at the intersection of machine learning, personalization, and product development, turning complex challenges into intuitive discovery experiences for millions of listeners.
What You'll Do
- Build and improve machine learning models that make Spotify Search more relevant, personalized, and engaging for listeners.
- Develop and optimize ranking and backend retrieval systems that help listeners discover music, videos, audiobooks, and other content.
- Explore emerging AI and agentic approaches to create more intuitive and conversational Search experiences.
- Design, implement, and evaluate machine learning solutions, taking ideas from early experimentation through production.
- Partner with engineers, product managers, designers, and researchers to identify opportunities and deliver meaningful improvements to Search.
- Use experimentation, data analysis, and performance metrics to understand model behavior, validate hypotheses, and improve the listener experience.
- Contribute to scalable machine learning infrastructure and engineering practices that support reliable, high-quality Search experiences.
- Share knowledge, challenge assumptions constructively, and help shape the technical direction of machine learning within the squad.
Who You Are
- You have experience building, deploying, and improving machine learning systems in production environments.
- You have a strong understanding of machine learning approaches for information retrieval, search ranking, recommendation systems, or personalization.
- You are proficient in Python and comfortable working with modern machine learning frameworks and data processing tools.
- You have experience and a desire to lean into backend engineering at Spotify scale.