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Spotify Machine Learning Engineer information

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$31.5K

$128.8K

$193.5K

How much do spotify machine learning engineer jobs pay per year?

As of Sep 2, 2026, the average yearly pay for spotify machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a Spotify machine learning engineer?

A Spotify Machine Learning Engineer designs, develops, and optimizes machine learning models to enhance Spotify’s user experience, recommendation systems, and audio analysis. They work with large-scale datasets, experiment with algorithms, and collaborate with data scientists, engineers, and product teams. The role involves deploying models to production, ensuring scalability, and improving personalization for millions of users worldwide. Strong skills in Python, TensorFlow/PyTorch, and cloud computing are essential.

What types of projects do Spotify machine learning engineers typically work on?

Spotify Machine Learning Engineers commonly work on projects involving personalized recommendations, music discovery algorithms, user behavior modeling, and content categorization. These projects often require collaboration with data scientists, backend engineers, and product teams to translate business objectives into scalable ML solutions. The role offers the opportunity to solve complex, real-world challenges at scale, using extensive data to enhance user engagement and product functionality. Engineers regularly experiment with new techniques and iterate on models to deliver more relevant, innovative experiences to Spotify’s global audience.

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

To thrive as a Spotify Machine Learning Engineer, you need strong expertise in machine learning, data analysis, programming (especially Python), and a relevant degree in computer science or a similar field. Proficiency with ML frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud or AWS), and experience with large-scale data processing tools are typically required. Strong problem-solving skills, collaboration, and clear communication help engineers work effectively within diverse, cross-functional teams. These skills enable innovation and ensure seamless integration of machine learning models that directly impact Spotify’s personalized user experiences.

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What job categories do people searching Spotify Machine Learning Engineer jobs look for?

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Spotify Machine Learning Engineer jobs near you
Infographic showing various Spotify Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Staff Machine Learning Engineer - Music Mission

Spotify

New York, NY

$227K - $324K/yr

Full-time

Medical, Retirement, PTO

Posted 20 days ago

Job description

The Music Mission team owns Spotify's end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale.

The DISCO Product Area is focused on building promotional tools that help artists reach more fans. Our products serve artists at scale through Spotify for Artists, and we're building on the momentum of Discovery Mode to help artists and their teams find new listeners when it matters most. As a Staff Machine Learning Engineer, you'll help shape the Machine Learning technical strategy for this high-impact area, partnering across engineering, product, data science, research, and design to create tools that help artists grow their audiences while supporting Spotify's core business.

What You'll Do
  • Help define and drive the Machine Learning engineering strategy for Discovery Mode and related royalty programs, translating product goals into scalable technical solutions.
  • Design, build, evaluate, ship, and refine production Machine Learning systems through hands-on development.
  • Provide technical leadership across complex ML initiatives, helping teams make thoughtful architectural and engineering decisions while balancing near- and long-term priorities.
  • Collaborate with user research, design, data science, product management, and engineering to build new product capabilities that strengthen connections between artists and fans.
  • Prototype new approaches and turn successful ideas into reliable, scalable solutions for Spotify for Artists customers.
  • Drive experimentation, optimization, testing, and tooling that improve the quality, reliability, and effectiveness of our Machine Learning systems.
  • Partner with engineers and Machine Learning practitioners across Spotify, including Music Tech Research and Personalization, to explore and develop new approaches to music promotion.
  • Help grow the technical capabilities of the broader engineering community through mentorship, knowledge sharing, and strong engineering practices.
Who You Are
  • You have deep experience with Machine Learning and a strong understanding of Machine Learning algorithms, modeling approaches, evaluation, and experimentation.
  • You have hands-on experience designing and implementing production Machine Learning systems at scale using languages such as Python, Java, Scala, or similar.
  • You can set technical direction for complex ML problems while remaining close to implementation and delivery.
  • You care about reliable software, data-informed development, disciplined experimentation, and building systems that perform effectively at scale.
  • You enjoy leading technically complex projects from idea through production and working closely with teammates and partners to deliver meaningful outcomes.
  • You are comfortable navigating ambiguity, evaluating trade-offs, and creating clarity on high-impact initiatives.
  • You communicate technical decisions and risks clearly and can build alignment with senior technical leaders and cross-functional partners.
  • You care about creating products that better serve artists and their teams, and you take a collaborative, team-first approach to helping others do their best work.
Where You'll Be
  • We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
  • This team operates within the Eastern time zone for collaboration.

The United States base range for this position is $227,495.00 - $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, paid flexible holidays, and paid sick leave. These ranges may be modified in the future

Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what's playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It's in our differences that we will find the power to keep revolutionizing the way the world listens.

At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we're here to support you in any way we can.

Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world's most popular audio streaming subscription service.

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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