Machine Learning Engineer, Personalization at Spotify

Boston, Massachusetts, United States

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$136,878 – $195,540Compensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, EntertainmentIndustries

Requirements

Strong background in machine learning, with experience and expertise in personalized machine learning algorithms, especially recommender systems
Hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages
Experience with XGBoost, TensorFlow is a plus
Care about agile software processes, data-driven development, reliability, and disciplined experimentation
Located within the North America region, operating within the Eastern Standard time zone for collaboration

Responsibilities

Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
Collaborate with a cross-functional agile team spanning user research, design, data science, product management, and engineering to build new product features that advance the mission to connect artists and fans in personalized and relevant ways
Prototype new approaches and production-ize solutions at scale for hundreds of millions of active users
Help drive optimization, testing, and tooling to improve quality
Be part of an active group of machine learning practitioners in New York (and across Spotify) collaborating with one another

Skills

Key technologies and capabilities for this role

Machine LearningRecommender SystemsPythonJavaScalaXGBoostTensorFlow

Questions & Answers

Common questions about this position

What is the salary range for this Machine Learning Engineer position?

The United States base range for this position is $136,878 - $195,540 plus equity.

What are the benefits offered for this role?

Benefits include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and paid sick leave.

Is this position remote or does it require being in an office?

The role offers flexibility to work where you work best within the North America region as long as there is a work location, with the team operating within the Eastern Standard time zone for collaboration.

What skills and experience are required for this role?

Candidates need a strong background in machine learning with expertise in personalized algorithms especially recommender systems, hands-on experience implementing production ML systems at scale in Java, Scala, Python or similar, plus experience with XGBoost or TensorFlow.

What kind of team will I be working with?

You'll collaborate with a cross-functional agile team spanning user research, design, data science, product management, and engineering, and be part of an active group of machine learning practitioners in New York and across Spotify.

Spotify

Digital music streaming service with podcasts

About Spotify

Spotify provides a digital music streaming service that allows users to access millions of songs and podcasts from various artists and creators. Users can choose between a free plan, which includes advertisements, and a premium subscription that offers an ad-free experience along with features like offline listening and higher sound quality. This tiered model caters to different user preferences and budgets. Spotify generates revenue through subscription fees from premium users and advertising from the free tier. Unlike its competitors, Spotify stands out with its extensive music library, user-friendly interface, and personalized playlists. The company's goal is to connect listeners with a wide range of audio content while supporting artists and advertisers.

Stockholms kommun, SwedenHeadquarters

2006Year Founded

$2,004.2MTotal Funding

IPOCompany Stage

Consumer Software, EntertainmentIndustries

10,001+Employees

Benefits

Extensive learning opportunities, through our dedicated team, GreenHouse

Global parental leave, six months off - fully paid - for all new parents

Flexible public holidays, swap days off according to your values and beliefs

Flexible share incentives letting you choose how you share in our success

All The Feels, our employee assistance program and self-care hub

Spotify On Tour, join your colleagues on trips to industry festivals and events

Risks

Accidental display of adult content may harm Spotify's reputation.

Creating its own music to avoid royalties could lead to legal issues.

Layoffs may affect Spotify's operational efficiency and employee morale.

Differentiation

Spotify offers a vast library of music and podcasts globally.

The platform's user-friendly interface enhances user experience and engagement.

Spotify's personalized playlists cater to individual user preferences.

Upsides

Spotify's AI-powered Wrapped feature enhances user engagement and personalization.

Expansion into political podcasting taps into new audience segments.

Growing podcast popularity in Africa presents expansion opportunities for Spotify.

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