In the heart of New York City, a dedicated team at Spotify is working to redefine how we interact with audio content. Their mission? To make listening feel effortless, personal, and joyful for billions of users worldwide. This isn’t just about creating apps; it’s about shaping experiences across every screen, platform, and integration where Spotify appears.
The Verbatim squad, nestled within the Enrichment & Content Intelligence product area, focuses on helping Spotify better understand audio, text, and visual content through machine learning. They develop technologies that power various experiences on the platform, from content skipping to transcription, moderation, and visual understanding. Operating at the intersection of large-scale machine learning and product innovation, this team collaborates closely with Product, Engineering, and Data Science teams to build intelligent systems that enhance user experiences.
Pioneering machine learning initiatives
As a member of the Verbatim squad, you would lead end-to-end machine learning initiatives, from ideation and prototyping through experimentation, deployment, and large-scale productionization. This role involves designing, developing, and deploying machine learning systems that operate across hundreds of millions of content signals using both real-time and batch processing architectures.
Your work would advance Spotify’s capabilities in natural language understandingmultimodal AIand content intelligence. You would build and evaluate LLM-powered solutions using modern prompting techniques, retrieval systems, and advanced model orchestration approaches. Additionally, you would define rigorous evaluation methodologies, including golden datasets, precision and recall frameworks, offline benchmarking, and online experimentation.
Collaboration and mentorship
Partnering closely with Product Managers, Engineering Managers, Staff Engineers, and Data Scientists, you would influence technical strategy and roadmap decisions. Your role would also involve mentoring engineers across the organization, helping to elevate machine learning engineering standards and best practices. You would contribute to the adoption of AI-assisted development workflows and tooling that improve team productivity and engineering effectiveness.
Essential skills and experience
To excel in this role, you should have solid experience developing and deploying machine learning systems in production environments. You should have successfully delivered large-scale machine learning architectures operating on substantial datasets and high-throughput production systems. Deep experience with machine learning, deep learning, and modern AI technologies is crucial.
Hands-on experience working with large language models and understanding how to evaluate, adapt, and deploy them effectively for real-world product challenges is essential. You should have experience building evaluation frameworks and can quantify model performance through robust experimentation and measurement techniques. The ability to navigate ambiguity and make thoughtful technical trade-offs that balance product impact, scalability, and engineering quality is also important.
Experience influencing technical direction across cross-functional teams and communicating complex machine learning concepts to diverse audiences is valuable. A passion for developing others and enjoying mentoring engineers through technical guidance and collaboration is highly regarded. Experience working with NLPprompt engineeringretrieval-augmented generation (RAG)vector databasesor multimodal machine learning systems is beneficial. Curiosity about emerging AI technologies and excitement about integrating tools such as Claude Code, Cursor, and other AI-assisted development capabilities into engineering workflows is a plus.
Work environment and benefits
This role is based in New York City, offering the flexibility to work where you work best. While there will be some in-person meetings, the role allows for flexibility to work from home. The United States base range for this position is $184,049–262,928 USD, plus equity. Benefits include health insurance, six-month paid parental leave, a 401(k) retirement plan, a monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave.
Spotify offers extensive learning opportunities through their dedicated team, GreenHouse. They provide flexible share incentives, global parental leave, an employee assistance program called All The Feels, and flexible public holidays. These benefits highlight Spotify’s commitment to supporting their employees’ well-being and professional growth.
