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职位Spotify

Machine Learning Engineer

Spotify

Machine Learning Engineer

Spotify

New York, NY

·

On-site

·

Full-time

·

2w ago

The Music Promotion team is building products that allow creators to promote their work to reach new audiences and create lasting connections with their fans.

We’re looking for a Machine Learning Engineer to help us build systems that more accurately understand the performance that promotion can have, giving customers actionable insights for building their promotion strategies, whether it’s a DIY artist or an industry-facing partner.

As an ML Engineer, you will help execute on strategies for understanding the factors that play a role in the performance of promoted tracks across the globe.

You’ll build data-driven solutions, as well as effective online and offline strategies to efficiently iterate and evaluate model approaches.

You’ll have access to a growing list of datasets, features and ML infrastructure to continually experiment and improve the model-based approach.

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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