Senior Machine Learning Engineer - Podcast at Spotify

New York, New York, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Podcasting, Technology, MediaIndustries

Requirements

5+ years of professional experience in machine learning, with expertise in building and productionizing ML systems at scale
Fluent in Python; experience with PyTorch or TensorFlow is a strong plus
Worked with large-scale data systems and owning end-to-end ML workflows (data ingestion to serving)
Hands-on experience with cloud platforms like GCP or AWS, and with ML infra tools such as Ray, Apache Beam, or Airflow
Experience, or strong interest, in agent-based systems and LLM integrations
Thrive in agile environments, care deeply about product impact, and bring a user-centered outlook to ML development
Bonus: Experience with content recommendation, interactive media formats, or real-time systems
Bonus: Led initiatives within an organization, expertly balancing trade-offs in large-scale systems, engaging with collaborators, and crafting clear, actionable roadmaps

Responsibilities

Lead the ML strategy for a 200+ person organization by defining and maintaining a clear roadmap for the Spotify for Creators and Megaphone apps, collaborating closely with engineers and PMs to align on product requirements and enhance impact
Advise leadership on ML initiatives, guiding prioritization and shaping decisions on the development and rollout of ML features
Serve as the liaison for ML efforts within the Podcast mission and ML engineers/PMs across Spotify, ensuring deep understanding of existing systems and facilitating their seamless integration into the Spotify for Creators product
Mentor engineers in ML practices to level up Podcast Mission’s capabilities in the space
Work closely with backend, data, and client engineers as well as PMs and designers to ship features that directly impact podcast engagement metrics
Prototype novel agentic workflows (e.g., multi-component pipelines or tool-using agents) and contribute to experimentation around Creator-Consumer interactivity
Own and evolve ML model lifecycle: data annotation, data pipeline construction, feature engineering, model training, deployment, and monitoring
Design, develop, fine-tune, and deploy machine learning systems that power podcast growth
Optimize models for scale and reliability using modern ML infra tools like Ray, Apache Beam, and Google Cloud Platform (GCP)
Lead with an experimentation attitude. Implement A/B tests and contribute to continuous model evaluation and improvement loops to productionize solutions at scale for millions of active podcast users
Participate in Spotify’s ML community: share findings, explore new tools and paradigms, and contribute to scaling ML standards across the company

Skills

Machine Learning

Foundational Models

Agentic Workflows

Data Pipelines

Data Annotation

ML Model Lifecycle

Prototyping

Feedback Loops

Real-time 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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