Description
The Personalization team makes deciding what to play next easier and more enjoyable for every listener. We're behind some of Spotify's most-loved features, such as Blend and Discover Weekly. We built them by understanding the world of music and podcasts better than anyone else.
We are looking for a Machine Learning Engineer to join the Personalization team. As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers across PZN in prototyping and productizing state-of-the-art ML at the intersection of recommendations and long-term user satisfaction.
Responsibilities
- Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development
- Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization
- Lead collaborations and align across PZN to integrate and A/B test mid-term signals in various recommendation systems
Requirements
- Strong background in machine learning, with expertise 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. Experience with PyTorch, Ray, Hugging Face and related tools is required
- Some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS
- Care about agile software processes, data-driven development, reliability, and disciplined experimentation
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North America and EMEA region as long as we have a work location
- This team operates within the Eastern Standard time zone for collaboration
Additional Information
The United States base range for this position is $227,495- $324,993 equity. The benefits available for this position include health insurance, six month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, paid sick leave.