Backend Engineer, Mimir, Personalization
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 2h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 5h ago
The date the source published, not the day we noticed it (2026-09-15). Last seen at its source 1h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $159k–225k/yr
Middle 50% of 2182 listings that do state pay — Engineering · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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lever employer's own board first seen 2h ago · last seen 1h ago
The listing
Spotify’s Personalization Mission makes it easier for fans and artists to connect in more relevant and meaningful ways. We build the technology behind personalized experiences across Spotify, helping listeners discover and engage with the content they love.
We’re looking for a Backend Engineer to join a team within our Personalization organization that builds foundational backend infrastructure powering recommendations across Spotify. Our systems help teams efficiently identify, retrieve, rank, and filter relevant content to create personalized experiences for millions of listeners around the world.
The team works on large-scale systems that support content and user representations, candidate generation, and centralized filtering for recommendations. Our technology is used across many of Spotify’s user-facing experiences, giving you the opport
What You'll Do
- Build, maintain, and evolve backend systems that support personalization and recommendations at Spotify scale.
- Develop infrastructure that enables efficient retrieval, ranking, and filtering of personalized content.
- Build platform capabilities that support candidate generation and representations of content and users.
- Design reliable, scalable, and performant services capable of supporting high-volume recommendation workloads.
- Partner with engineers and teams across Spotify to understand their needs and build reusable platform solutions.
- Improve the reliability, observability, maintainability, and operational performance of the systems the team owns.
- Participate in technical design discussions and contribute to architectural decisions as our platforms continue to evolve.
Who You Are
- You have professional experience building and operating backend systems in production.
- You have experience with distributed systems, APIs, data-intensive applications, or large-scale service architectures.
- You’re comfortable working with systems where reliability, latency, and scalability matter.
- You can independently own engineering projects while collaborating effectively with engineers across teams.
- You’re interested in the infrastructure behind recommendation and personalization systems; prior machine learning experience is helpful but not required.
- You enjoy solving platform-level problems and building systems that other engineering teams depend on.
- You care about writing maintainable code, making thoughtful technical decisions, and continuously improving production systems.
Where You'll Be
- We are a distributed workforce enabling our band members to find a work mode that is best for them!
- Where in the world? For this role, it can be anywhere in the North America region in which we have a work location
- Prefer to work in an office environment? Prefer to work from home instead? Not a problem! We have plenty of options for your working preferences. Find more information about our Work From Anywhere options here.
- Working hours? We operate within the Eastern Standard time zone for collaboration.