Machine Learning Engineer, Personalization
Spotify
Machine Learning Engineer, Personalization
Spotify
full-time
Posted: December 15, 2025
Number of Vacancies: 1
Job Description
The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like “Home” and “Search” as well as original playlists such as “Discover Weekly” and “Daily Mix.”
Personalization’s Minesweeper squad produces Human Understandable Language Knowledge to enrich music and talk content understanding. We use AI and ML techniques, including Large Language Models, to understand music, podcasts and audiobooks, building reliable, scalable systems to distribute that knowledge to Spotify internal teams, users, and creators. We are looking for a Machine Learning Engineer to join our team and help build the future of music, podcast and audiobook listening experiences for millions of listeners at Spotify. This is a unique opportunity to help develop and shape Spotify content enrichment, and recommendations. You’ll grow your skills in ML engineering at scale, work with a cross-functional team of Data Engineers, Backend Engineers, and researchers, and join a motivated and supportive team.
Locations
- New York, New York, United States
Salary
Salary details available upon request
Estimated Salary Rangemedium confidence
220,000 - 400,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine learningintermediate
- Large Language Modelsintermediate
- Pythonintermediate
- Scalaintermediate
- Javaintermediate
- SQLintermediate
- Cloud platforms (GCP or AWS)intermediate
- Data pipelinesintermediate
- Dataflowintermediate
- Apache Beamintermediate
- Sparkintermediate
- PyTorchintermediate
- TensorFlowintermediate
- Rayintermediate
- TFXintermediate
- Agile software processesintermediate
- Data-driven developmentintermediate
Required Qualifications
- Strong background in machine learning, especially experience with Large Language Models (experience)
- Professional experience in applied machine learning (experience)
- Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, with Python experience required) and cloud platforms (GCP or AWS) (experience)
- Hands-on experience implementing or prototyping machine learning systems at scale (experience)
- 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 (experience)
- Care about agile software processes, data-driven development, reliability, and disciplined experimentation (experience)
- Experience and passion for fostering collaborative teams (experience)
Preferred Qualifications
- Experience with PyTorch, TensorFlow, and/or other scalable Machine learning frameworks (experience)
- Experience with Ray or TFX (experience)
- Experience with architecting near real time pipelines (experience)
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
Benefits
- general: 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
- general: This team operates within the Eastern Standard time zone for collaboration
Tags & Categories
Machine Learning Engineer, Personalization
Spotify
Machine Learning Engineer, Personalization
Spotify
full-time
Posted: December 15, 2025
Number of Vacancies: 1
Job Description
The Personalization team makes deciding what to play next on Spotify easier and more enjoyable for every listener. We seek to understand the world of music, podcasts, and audiobooks better than anyone else so that we can make great recommendations to every individual person and keep the world listening. Every day, hundreds of millions of people all over the world use the products we build which include destinations like “Home” and “Search” as well as original playlists such as “Discover Weekly” and “Daily Mix.”
Personalization’s Minesweeper squad produces Human Understandable Language Knowledge to enrich music and talk content understanding. We use AI and ML techniques, including Large Language Models, to understand music, podcasts and audiobooks, building reliable, scalable systems to distribute that knowledge to Spotify internal teams, users, and creators. We are looking for a Machine Learning Engineer to join our team and help build the future of music, podcast and audiobook listening experiences for millions of listeners at Spotify. This is a unique opportunity to help develop and shape Spotify content enrichment, and recommendations. You’ll grow your skills in ML engineering at scale, work with a cross-functional team of Data Engineers, Backend Engineers, and researchers, and join a motivated and supportive team.
Locations
- New York, New York, United States
Salary
Salary details available upon request
Estimated Salary Rangemedium confidence
220,000 - 400,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine learningintermediate
- Large Language Modelsintermediate
- Pythonintermediate
- Scalaintermediate
- Javaintermediate
- SQLintermediate
- Cloud platforms (GCP or AWS)intermediate
- Data pipelinesintermediate
- Dataflowintermediate
- Apache Beamintermediate
- Sparkintermediate
- PyTorchintermediate
- TensorFlowintermediate
- Rayintermediate
- TFXintermediate
- Agile software processesintermediate
- Data-driven developmentintermediate
Required Qualifications
- Strong background in machine learning, especially experience with Large Language Models (experience)
- Professional experience in applied machine learning (experience)
- Extensive experience working in a product and data-driven environment (Python, Scala, Java, SQL, with Python experience required) and cloud platforms (GCP or AWS) (experience)
- Hands-on experience implementing or prototyping machine learning systems at scale (experience)
- 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 (experience)
- Care about agile software processes, data-driven development, reliability, and disciplined experimentation (experience)
- Experience and passion for fostering collaborative teams (experience)
Preferred Qualifications
- Experience with PyTorch, TensorFlow, and/or other scalable Machine learning frameworks (experience)
- Experience with Ray or TFX (experience)
- Experience with architecting near real time pipelines (experience)
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
Benefits
- general: 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
- general: This team operates within the Eastern Standard time zone for collaboration
Tags & Categories