Senior Staff Machine Learning Engineer, Notifications

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet.

Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.

For more information, visit www.redditinc.com .

The Notifications Relevance team at Reddit is building the next generation of notifications focused on delivering the right content to the right user at the right time using the right channel (push notification, email digest and in-app).

We are the second largest growth lever at Reddit and a core component to understanding how to delight our current user base and bring new users to discover all that Reddit has to offer.

Redditors produce the most amazing content about every niche topic in the world. Leveraging machine learning and large-scale system development, we process hundreds of millions of posts and user activities to provide personalized recommendations for tens of millions of users.

As a Senior Staff, you will design and build a large-scale system that powers end-to-end recommendation systems at scale. You’ll work across multiple areas of the stack, including budget optimization, retrieval, ranking, features, measurement, LLM-based answers, etc, partnering deeply with product, org leads, and other XFN to deliver reliable, high quality systems that can help Reddit Notifications push the boundary on state of the art.

What You’ll Do

Contribute to advancing Reddits growth by designing and implementing content discovery algorithms that prioritize a seamless and highly personalized user experience.

Deeply understand the Reddit Notifications product and drive the vision for the notifications relevance team. Enhance core recommendation capabilities, including candidate retrieval, ranking models, and budgeting optimization, while designing and testing new pipeline components.