Machine Learning Engineer - Personalization
TLDR
Contribute to designing and optimizing innovative recommendation systems used by hundreds of millions of Spotify users, enhancing their listening experiences with personalized content.
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.
You have a background in machine learning, enjoy applying theory to develop real-world applications, with experience in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
You have 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.
You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
We offer you the 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.
This team operates within the Eastern Standard time zone for collaboration.
Benefits
Health Insurance
The benefits available for this position include health insurance.
Monthly meal allowance
Paid Parental Leave
Six month paid parental leave.
Paid Time Off
23 paid days off, 13 paid flexible holidays, paid sick leave.
Spotify is an audio streaming platform that delivers an extensive catalog of music, podcasts, and audiobooks, catering to hundreds of millions of users globally. It empowers artists by providing them with the means to monetize their creativity while offering fans unparalleled access to a diverse array of content, all driven by a passion for sound.
- Founded
- Founded 2006
- Employees
- 500+ employees
- Industry
- Media
- Total raised
- $2.6B raised