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Spotify Machine Learning Engineer Jobs (NOW HIRING)

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Machine Learning Engineer

Manhattan, NY · On-site

Machine Learning Engineers build production grade machine learning algorithms that operate in real ... Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc). * Experience building ...

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

As of Jun 7, 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 job?

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 are the key skills and qualifications needed to thrive in the Spotify Machine Learning Engineer position, and why are they important?

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.

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.

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What job categories do people searching Spotify Machine Learning Engineer jobs look for? The top searched job categories for Spotify Machine Learning Engineer jobs are:
Spotify Machine Learning Engineer jobs near you
Infographic showing various Spotify Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 89% Full Time, 8% Part Time, and 3% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer I, Personalization , Minesweeper

Spotify

Remote

$117K - $140K/yr

Full-time

Posted 27 days ago

Job description

Job Summary:
Spotify is a leading audio streaming service that seeks to enhance user experiences through personalized content recommendations. They are looking for a Machine Learning Engineer I to join their Personalization team, focusing on improving language understanding and content enrichment for music, podcasts, and audiobooks using AI and ML techniques.
Responsibilities:
• Utilize in-house and 3rd party LLMs to solve language understanding problems
• Employ techniques such as fine-tuning and RAG to improve models
• Contribute to designing, building, evaluating, shipping, and refining Spotify’s product by hands-on ML development
• Help drive optimization, testing, and tooling to improve quality of our content enrichment assets
• Collaborate with cross-functional teams of MLEs, data and backend engineers, and other stakeholders including tech research, data science, and product to develop new features and technologies
• Be a participant in our AI Foundation’s ML community and work collaboratively and efficiently within our existing platforms and systems Perform data analysis to establish baselines and inform product decisions
• Stay up-to-date on the latest machine learning algorithms and techniques
Qualifications:
Required:
• You have a strong background in machine learning, especially experience with Large Language Models
• You have professional experience in applied machine learning
• Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, with Python experience required) and cloud platforms (GCP or AWS)
• You have some hands-on experience implementing or prototyping machine learning systems at scale
• You have experience architecting data pipelines and are self-sufficient in getting the data you need to build and evaluate models, using tools like Dataflow, Apache Beam, or Spark
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation
• You have experience and passion for fostering collaborative teams
• Experience with PyTorch, TensorFlow, and/or other scalable Machine learning frameworks
Preferred:
• Experience with Ray or TFX
• Bonus if you have experience with architecting near real time pipelines
Company:
Spotify is a commercial music streaming service that provides restricted digital content from a range of record labels and artists. Founded in 2006, the company is headquartered in Stockholm, SWE, with a team of 5001-10000 employees. The company is currently Late Stage.

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