Machine Learning Engineer II

Summary

Join Spotify's Personalization team and be part of the Next Generation Sessions (NextGen) product area, reimagining listening experiences beyond playlists. As an MLE II / AI Engineer, you will invent new AI-powered listening experiences, explore emerging AI capabilities, prototype end-to-end products, and bring new features to millions of users. This fast-paced role requires collaboration with cross-functional teams and staying at the forefront of AI in music and talk content. You will rapidly prototype and ship AI-powered experiences, explore new models and tools, promote best practices in AI engineering, and leverage AI coding assistants. The role demands a keen eye for software quality and collaboration with various teams to bring ideas from concept to launch. Growth opportunities are abundant with access to Spotify's career development resources.

Requirements

• You’re a full-stack AI prototyper: building your own projects with modern AI tools, experimenting fast, and iterating based on feedback
• You’re fully plugged into the AI ecosystem—active in online communities, exploring open-source repos, reading papers, trying every new tool you can get your hands on
• You think end-to-end, across the stack—from designing user interactions, to wiring up backends, to building models, to deployment considerations—because you want to see ideas come to life
• You have a working knowledge of machine learning fundamentals and hands-on experience with Python, Java, or Scala and modern ML frameworks like PyTorch or TensorFlow
• You have experience fine-tuning and evaluating LLMs
• You have knowledge and/or experience building workflows that integrate LLMs and data into autonomous, multi-step workflows
• You have extensive experience crafting prompts to get the results you’re after. You know how to write, improve, and test your prompts to extract value out of LLMs
• You understand the importance of critically reviewing AI-generated code for correctness, quality, and alignment with best practices
• You may have studied AI formally—or you may have taught yourself through hands-on building and deep curiosity
• You thrive in collaborative, interdisciplinary environments and are eager to learn from more experienced engineers
• You bring contagious enthusiasm, a creative mindset, and a strong drive to shape the future of AI-powered products

Responsibilities

• Rapidly prototype, iterate, and ship AI-powered music and podcast recommendation experiences using the latest capabilities of LLMs, agent frameworks, and Spotify’s recommender systems
• Continuously explore and evaluate new models, tools, libraries, and product trends—bringing fresh ideas into the team from the frontiers of AI and open-source innovation
• Promote and model best practices in AI engineering—including the use of LLMs and agents to power products, advanced evaluation strategies, and AI-assisted coding tools
• Leverage AI coding assistants to rapidly prototype full-stack MVPs
• Collaborate with cross-functional partners—including design, user research, product, data science, tech research, and engineering—to bring new ideas from concept to launch
• Develop a keen eye for software quality, learning to critically evaluate AI-generated code to ensure it meets Spotify's high standards for correctness, performance, and engineering best practices
• Grow your skills with access to Spotify’s comprehensive career development resources and encouragement to develop across disciplines
• Build a strong foundation and culture in AI engineering by leveraging the state of the art, learning from mentors, pairing with Staff engineers, and shipping code that reaches hundreds of millions of users

Benefits

• Health insurance
• Six month paid parental leave
• 401(k) retirement plan
• Monthly meal allowance
• 23 paid days off
• 13 paid flexible holidays
• Paid sick leave