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トレンド企業

トレンド企業

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求人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.

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

Spotifyについて

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

従業員数

Stockholm

本社所在地

$23B

企業価値

レビュー

4.1

10件のレビュー

ワークライフバランス

3.8

報酬

4.2

企業文化

4.3

キャリア

3.9

経営陣

2.8

78%

友人に勧める

良い点

Flexible working hours and remote options

Great team culture and collaborative environment

Innovative projects and creative freedom

改善点

High workload and performance pressure

Fast-paced environment can be overwhelming

Management issues and disorganization

給与レンジ

17件のデータ

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Associate Data Scientist

0件のレポート

$142,458

年収総額

基本給

-

ストック

-

ボーナス

-

$121,089

$163,827

面接体験

3件の面接

難易度

3.0

/ 5

期間

14-28週間

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit