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Spotify Machine Learning Jobs (NOW HIRING)

Spotify

Research Scientist - Personalization

Boston, MA · On-site

$150 - $200/hr

... with Spotify's personalization strategy * Mentor others and contribute to a strong, curious, and collaborative research culture Who You Are * You have a Master's or PhD in machine learning ...

Spotify

Research Scientist - Personalization

Boston, MA · On-site

$133K - $190K/yr

... with Spotify's personalization strategy * Mentor others and contribute to a strong, curious, and collaborative research culture Who You Are * You have a Master's or PhD in machine learning ...

Spotify

Research Scientist - Personalization

Boston, MA · On-site +1

$133K - $190K/yr

... with Spotify's personalization strategy * Mentor others and contribute to a strong, curious, and collaborative research culture Who You Are * You have a Master's or PhD in machine learning ...

Spotify

Research Scientist - Personalization

New York, NY · Remote

$133K - $190K/yr

... with Spotify's personalization strategy * Mentor others and contribute to a strong, curious, and collaborative research culture Who You Are * You have a Master's or PhD in machine learning ...

Spotify

Research Scientist - Personalization

Boston, MA · Remote

$133K - $190K/yr

... with Spotify's personalization strategy * Mentor others and contribute to a strong, curious, and collaborative research culture Who You Are * You have a Master's or PhD in machine learning ...

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Spotify Machine Learning information

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$25.5K

$42.6K

$88K

How much do spotify machine learning jobs pay per year?

As of Sep 8, 2026, the average yearly pay for spotify machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What does a Spotify machine learning engineer do?

A Spotify Machine Learning Engineer designs, builds, and deploys machine learning models to enhance the Spotify platform. Their work involves analyzing large datasets to improve music recommendations, personalize user experiences, and optimize features like search and playlist generation. They collaborate with data scientists, developers, and product teams to solve complex problems using AI and data-driven techniques. This role requires expertise in programming, data analysis, and machine learning frameworks.

How does a Spotify machine learning engineer typically collaborate with product and engineering teams?

As a Machine Learning Engineer at Spotify, you'll work closely with cross-functional teams, including product managers, software engineers, and data scientists, to design and deploy models that enhance user experience. Collaboration often involves participating in brainstorming sessions, sharing model insights, and aligning on product goals to ensure your solutions are impactful and scalable. You'll also routinely communicate your findings and recommendations, helping stakeholders understand complex technical concepts. This collaborative environment encourages innovation and helps drive Spotify's data-driven features, such as personalized playlists and recommendations.

What are the key skills and qualifications needed to thrive as a Spotify machine learning engineer, and why are they important?

To thrive as a Spotify Machine Learning Engineer, you need strong expertise in machine learning algorithms, data analysis, and programming (often in Python), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and big data platforms like Apache Spark is essential, as well as experience with cloud computing environments. Collaboration, creativity, and effective communication are standout soft skills for working on cross-functional teams and translating complex data insights into impactful solutions. These skills and qualities are crucial to developing personalized, scalable, and innovative features that enhance the Spotify user experience.

What is the difference between Spotify Machine Learning vs Data Scientist?

AspectSpotify Machine LearningData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with ML frameworksDegree in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentFocus on developing ML models for music streaming, personalization, and recommendationsAnalyze data, generate insights, and support decision-making across various business units
Employer & Industry UsagePrimarily in tech and entertainment industries, especially streaming servicesWidely used across industries including tech, finance, healthcare, and marketing

Spotify Machine Learning specialists focus on building and deploying ML models to enhance user experience on the platform, while Data Scientists analyze data to inform business strategies. Both roles require strong technical skills, but their core responsibilities differ in application and scope.

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Infographic showing various Spotify Machine Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Staff Machine Learning Engineer - Content Intelligence

Spotify

New York, NY • On-site

Full-time

Medical, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Key responsibilities

  • Build and scale machine learning systems that generate deep understanding of content across modalities

  • Develop models for classification, tagging, semantic understanding, and content enrichment

  • Design systems that make content intelligence signals available to downstream teams and products

Job description

We design Spotify's consumer experience - end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.

The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continues to grow-driven by advances in AI and new creation tools-we're building intelligent systems that can evaluate, manage, and route content reliably at global scale.

We're seeking a Staff Machine Learning Engineer to build and scale foundational ML systems that power content understanding across Spotify. In this role, you'll work on systems that generate deep, machine-readable understanding of content across audio, video, text, and images-enabling automation, improving quality, and unlocking new product experiences. This work is central to delivering safe, high-quality, and differentiated experiences for millions of listeners and creators worldwide.

What You Will Do

  • Build and scale machine learning systems that generate deep understanding of content across modalities

  • Develop models for classification, tagging, semantic understanding, and content enrichment

  • Create high quality content enrichment at scale using LLMs and agentic systems.

  • Design systems that make content intelligence signals available to downstream teams and products

  • Improve automation for content quality, safety, and metadata enrichment at scale

  • Collaborate with product, policy, and engineering teams to translate content intelligence into user impact

  • Contribute to evaluation frameworks, data pipelines, and annotation systems

  • Support rapid experimentation to prototype and launch new types of content signals

  • Help improve system reliability, scalability, and performance across large datasets

Who You Are

  • You have experience building and deploying machine learning systems in production

  • You are comfortable working with ML frameworks such as PyTorch, TensorFlow, or similar

  • You have experience working with large datasets and care about data quality and evaluation

  • You are interested in or have worked with multimodal machine learning

  • You understand how to design systems that balance automation with quality and user experience

  • You are comfortable working on complex problems with evolving requirements

  • You think in systems and understand how models connect to product outcomes

  • You communicate clearly and work well across technical and non-technical teams

Where You Will Be
  • This role is based in New York, NY
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

The United States base range for this position is 227,495-324,993 USD, plus equity. The benefits available for this position 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. These ranges may be modified in the future.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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