Machine Learning Engineer - Personalization
New York, NYRemote
Summary
Develops and scales ML reward signals for Spotify's recommendation systems like playlists and search. Leads cross-team collaborations, A/B testing, and best practices in production ML systems using transformers, generative AI, and distributed frameworks.
About the role
What You'll Do
- Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
- Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
Who You Are
- Background in machine learning, applying theory to real-world applications, experience in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
- Hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
- Hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
- Some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, Scio, and cloud platforms like GCP or AWS.
- Care about agile software processes, data-driven development, reliability, and disciplined experimentation.
Skills
Machine LearningTransformersGenerative AILarge Language ModelsPythonJavaScalaApache SparkApache BeamGCPAWSScio