Senior Machine Learning Infrastructure Engineer, Music Full-time

We are looking for a Machine Learning Infrastructure Engineer to help us build the next generation of AI-based audio understanding technologies. Our team expands the state of the art in AI-based machine listening technology, which enables new ways to search, re-use, explore, understand, and recommend music. We build products for Spotify users, artists, music labels, publishers, managers, advertisers, and more. Most of our projects cut across all of Spotify and have company-wide impact. We develop features to improve products and lay the foundations for exciting new product opportunities.

What You’ll Do

• Build massive data processing pipelines to run ML models on audio at petabyte-scale
• Work cross-functionally with other engineers, research scientists, and product managers to build audio ML research into Spotify’s products to serve hundreds of millions of users
• Build best-in-class infrastructure and tooling to support and accelerate model training
• Work closely with research scientists to debug, optimize, and convert ML models for deployment
• Debug problems across the entire stack, from low-level debugging to high-level system design
• Collaborate with customer teams to deploy our research in products around Spotify, in backend, data, mobile, core, and other code bases
• Scope the feasibility of projects through quick prototyping to assess performance, quality, time and cost
• Help maintain crucial pieces of Spotify-owned open-source audio software infrastructure like Pedalboard, Basic Pitch, and more

Who You Are

• You have professional experience working with machine learning systems
• You have a very strong grasp of Python, but are happy to work in languages like Java, Scala, C++, and others as necessary
• You have very strong communication skills and can collaborate effectively with ML researchers, product stakeholders, and executives across various geographies
• You have strong systems fundamentals and can debug problems down to the operating system level
• You have a good understanding of performance and can design and engineer systems that scale without breaking the bank
• You have experience debugging, profiling, optimizing, or deploying ML models
• You have worked with cloud platforms like GCP, AWS, or Azure
• You have proven experience implementing and maintaining large-scale production software systems
• You are interested in learning more about audio processing and music information retrieval and you’re excited about building products that use such technologies
• You are willing to go on call to support the systems we build, and are willing to build systems for reliability to avoid on-call fatigue. (The team averages 1 incident per quarter.)
• Experience with deep learning techniques for content based processing (audio, image, video data) is a plus

Where You’ll Be

• This role will be located in our London or Stockholm office