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职位Spotify

Backend Engineer, Music

Spotify

Backend Engineer, Music

Spotify

New York, NY

·

On-site

·

Full-time

·

3w ago

必备技能

Machine Learning

In the Music Mission, we build the tools and services that enable creators to express themselves, promote their work, and connect with fans. Discovery Mode is a key promotional tool that helps artists, labels, and licensors grow their audience while maintaining a high-quality listener experience.

We are looking for a Backend focused engineer to join the OASIS team. OASIS builds and operates the systems that power promotion delivery and optimization within Discovery Mode. Our work ensures that promotional content isn’t just "surfaced", but is intelligently allocated by balancing complex, competing objectives across our entire ecosystem.

The team is distributed and highly collaborative, working closely with Personalization (PZN) to serve high-quality promotion signals. You’ll be part of a small, impactful group of engineers across data and machine learning, owning a core piece of infrastructure that enables promotion delivery at scale.

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关于Spotify

Spotify

Spotify

Public

Spotify is a Swedish audio streaming and media service provider founded in April 2006 by Daniel Ek and Martin Lorentzon. As of December 2025, it was one of the largest providers of music streaming services, with over 751 million monthly active users comprising 290 million paying subscribers.

5,001-10,000

员工数

Stockholm

总部位置

$23B

企业估值

评价

4.1

10条评价

工作生活平衡

3.8

薪酬

4.2

企业文化

4.3

职业发展

3.9

管理层

2.8

78%

推荐给朋友

优点

Flexible working hours and remote options

Great team culture and collaborative environment

Innovative projects and creative freedom

缺点

High workload and performance pressure

Fast-paced environment can be overwhelming

Management issues and disorganization

薪资范围

17个数据点

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Associate Data Scientist

0份报告

$142,458

年薪总额

基本工资

-

股票

-

奖金

-

$121,089

$163,827

面试经验

3次面试

难度

3.0

/ 5

时长

14-28周

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit