Backend Engineer - Learning Infrastructure
The Hendrix Feature team is dedicated to developing a robust, Spotify-wide platform for machine learning features. This platform streamlines the productionization of ML models by mitigating the incidental complexities involved in creating and maintaining Features, both in their lineage, offline states, and online states.
- Identify collaboration opportunities to support the team and ensure successful collaboration with other teams and stakeholders
- Is a squad-level expert in a primary domain or drives solutions to a broad set of problems across multiple domains for the squad
- Delivers on large, complex tasks for features as defined and on schedule, managing all dependencies and communication cross-functionally
- Mentor other engineers, developing their skills and setting an example for engineering standards at Spotify
- Consider the inter-squad connections between features and the rest of the machine learning product area, and Spotify wide machine learning ecosystem
- You have 3+ years of hands-on experience implementing production machine learning infrastructure at scale in Python, Java, Scala, or similar languages
- You have a general understanding of data processing concepts
- You have experience with agile software processes and modular code design following industry standards
- You have deep experience with developing backend systems at scale and optimizing for performance
- This role is based in Stockholm
- We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home. We ask that you come in 2-3 times per week
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Spotify is one of the largest online music streaming service providers founded in 2006 by Daniel Ek and Martin Lorentzon. As of March 2024, Spotify has over 615 million monthly active users, including 239 million paying subscribers around the world.
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