Key skills
Machine learningStatisticsOptimizationSequential modelsTransformersGenerative AILarge language modelsProduction machine learning systemsPersonalization systemsRecommendation systemsJavaScalaPythonPyTorchRayHugging FaceApache BeamApache SparkScioGoogle Cloud PlatformAmazon Web ServicesAgile software processesData-driven developmentAIMachine LearningMLSparkAWSGCPAgile
About this role
Spotify is a leading music streaming service, and they are seeking a Senior Machine Learning Engineer to join their Personalization team. The role involves designing, developing, and evaluating recommendation models to enhance user experiences across Spotify's platforms.
Responsibilities:
- Contribute to the design, development, evaluation, and iteration of recommendation models — including candidate generation, ranking, and embedding models — powering music surfaces at scale
- Drive hands-on ML development to improve reward signals and recommendation quality across Home, Now Playing, and other core surfaces
- Contribute to the team's adoption of generative recommendation models, partnering with ML and AI infrastructure teams
- Promote best practices in ML systems development, testing, and experimentation within the team
- Collaborate with Data Science, Product, and Design partners to define success metrics, run A/B experiments, and translate insights into product improvements
- Partner with teams across Personalization to integrate and test new signals in recommendation systems
Requirements:
- You have a strong background in machine learning and enjoy applying theory to real-world applications, with expertise in statistics and optimization — particularly sequential models, transformers, generative AI, and LLMs
- You have hands-on experience building and shipping production machine learning systems at scale, ideally in personalization or recommendation systems
- You have experience implementing ML systems in Java, Scala, Python, or similar languages
- You have some experience with large-scale distributed data processing frameworks such as Apache Beam, Apache Spark, or Scio, and cloud platforms like GCP or AWS
- You have experience collaborating across teams on complex ML projects and navigating cross-functional stakeholders
- You care about agile software processes, data-driven development, reliability, and disciplined experimentation
- Familiarity with PyTorch, Ray or Hugging Face is a plus