Staff Machine Learning Engineer, Personalization
SpotifyAudio Streaming company
New York, United StatesLead
TPG
Goldman Sachs
Northzone
Accel
DST Global
Founders Fund
Data & AI
About the role
TL;DR
Build and deploy ML models for Spotify's personalization features, focusing on recommendations and LLMs.
- •The Personalization team at Spotify builds features like Blend and Discover Weekly to make music and podcast discovery easier and more enjoyable.
- •As a Staff Machine Learning Engineer, you'll shape the future of personalized discovery and engagement by working with recommendation systems, LLMs, and production-scale ML infrastructure.
- •Key Responsibilities Own and improve ML models and systems for the Home feed and Shortcuts experience.
- •Design, build, and ship personalized recommendations for millions of listeners globally.
- •Train, fine-tune, and optimize large language models.
- •Partner with product managers, engineers, and designers to execute experimentation strategies.
- •Improve ML platform capabilities and production systems.
- •Requirements 8+ years of experience building and deploying ML systems in production.
- •Deep expertise in recommendation systems, ranking models, or personalization platforms.
- •Strong proficiency in Python and hands-on experience with PyTorch.
- •Experience with large language model training, fine-tuning, and optimization techniques.
- •Experience operating large-scale inference systems and distributed ML workloads.
Required skills
PythonPyTorchLLMsNLPscikit-learnSparkAirflowBigQueryKubernetesDockerGitLinux
Nice-to-have skills
TensorFlowAWSGoogle CloudAzurePostgreSQLMySQLRedis
Domain expertise
entertainment-musicaiproductivity
Tech stack
PythonPyTorchTensorFlowscikit-learnNLPLLMsAWSGoogle CloudAzureSparkAirflowBigQueryPostgreSQLMySQLRedisKubernetesDockerGitLinuxJiraConfluenceREST APIgRPC