Senior Machine Learning Infrastructure Engineer, Music
3 weeks ago
We are seeking a highly skilled Machine Learning Infrastructure Engineer to join our team at Spotify. As a key member of our audio technology team, you will play a crucial role in building the next generation of AI-based audio understanding technologies.
Key Responsibilities- Design and Develop Massive Data Processing Pipelines: Build scalable data processing pipelines to run machine learning models on audio data at petabyte-scale.
- Collaborate with Cross-Functional Teams: Work closely with engineers, research scientists, and product managers to integrate audio ML research into Spotify's products, serving hundreds of millions of users.
- Develop Best-in-Class Infrastructure and Tooling: Design and implement best-in-class infrastructure and tooling to support and accelerate model training.
- Debug and Optimize ML Models: Work with research scientists to debug, optimize, and convert ML models for deployment.
- Debug Problems Across the Entire Stack: Collaborate with customer teams to deploy research in products across Spotify, including backend, data, mobile, core, and other code bases.
- Scope Project Feasibility: Conduct quick prototyping to assess project performance, quality, time, and cost.
- Maintain Open-Source Audio Software Infrastructure: Contribute to the maintenance of crucial pieces of Spotify-owned open-source audio software infrastructure.
- Professional Experience with Machine Learning Systems: You have hands-on experience working with machine learning systems.
- Strong Programming Skills: You have a strong grasp of Python, but are also proficient in languages like Java, Scala, C++, and others as necessary.
- Effective Communication and Collaboration: You have excellent communication skills and can collaborate effectively with ML researchers, product stakeholders, and executives across various geographies.
- Strong Systems Fundamentals: You have a solid understanding of systems fundamentals and can debug problems down to the operating system level.
- Performance Optimization: You have a good understanding of performance and can design and engineer systems that scale without breaking the bank.
- Experience with Cloud Platforms: You have experience working with cloud platforms like GCP, AWS, or Azure.
- Proven Experience with Large-Scale Production Software Systems: You have a proven track record of implementing and maintaining large-scale production software systems.
- Interest in Audio Processing and Music Information Retrieval: You are interested in learning more about audio processing and music information retrieval and are excited about building products that use such technologies.
- Willingness to Go On Call: You are willing to go on call to support the systems you build and are committed to building systems for reliability to avoid on-call fatigue.
- Deep Learning Techniques: Experience with deep learning techniques for content-based processing (audio, image, video data) is a plus.
This role will be located in our London or Stockholm office.
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