Staff Machine Learning Engineer, GenRecs at Spotify

New York, New York, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Media StreamingIndustries

Requirements

Strong background in machine learning and recommender systems, bridging research and end-user impact
Production experience developing large-scale machine learning systems in Java, Scala, Python, or similar languages (PyTorch, Tensorflow, JAX is a strong plus)
Hands-on experience training and operating transformer models in production settings, or strong interest in doing so
Experience leading projects from start to finish, working closely with teams and peers
Comfortable dealing with ambiguity on high-impact projects
Strong communicator and systems thinker, able to drive alignment and influence across technical and product stakeholders
Knowledge of agile software processes, data-driven development, reliability, and disciplined experimentation
Stays current on ML trends and eager to apply emerging ideas
Passionate about enriching the listening experience for users

Responsibilities

Contribute to defining the machine learning technical strategy at the intersection of generative recommenders and foundational user modeling
Collaborate with a cross-functional agile team (user research, design, data science, product management, engineering) to build new product features
Provide expert technical leadership and direction to accelerate development, ensure scalability, and push boundaries of current methods
Design, build, evaluate, ship, and refine Spotify’s personalization products through hands-on ML development
Prototype new modeling approaches and productionize solutions at scale for hundreds of millions of active users
Promote and role-model best practices of ML model development, testing, evaluation within the team and organization
Engage with the broader ML community within Spotify and stay current with ML research to inspire and evolve approaches

Skills

Machine Learning

Recommender Systems

Generative AI

LLMs

User Modeling

Scalable Systems

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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