Senior Machine Learning Engineer, Feed Relevance

Reddit, Inc.

full-time

Posted on: 9/6/2025

Location: 🇺🇸 United States

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💰 $216,700 - $303,400 per year

Senior

GoPythonSQL

About the role

Build the pipelines and low-latency services behind one of the largest personalized feeds on the internet
Turn modeling ideas into production systems, wire up new features and ranking signals, and design experiments that let us ship with confidence
Write efficient, scalable and maintainable code that will help consistently deliver highly personalized experiences to Reddit users
Design and implement components of our recommender systems to adapt to user signals and optimize for long term user satisfaction; potentially including user targeting and segmentation, candidate retrieval, reinforcement learning, feature engineering, and prediction models
Follow data-driven design principles to develop hypotheses, test them via well designed experiments, and analyze the results to learn and iterate
Champion and drive engineering processes and best practices
Collaborate across disciplines and with other ML teams at Reddit to find technical solutions to complex challenges

4+ years of experience as a machine learning engineer or software engineer developing backend / infrastructure at scale, using Go, Python, or any object oriented programming language
2+ years building data or model-serving pipelines at scale
Experience working with recommender systems or other ML-driven products
Familiar with software engineering best practices such as unit testing and code reviews, design, and documentation
Skilled at diving into data to debug system performance and develop a deeper understanding of how users are engaging with the product; proficient with SQL and data analysis
Passionate about building delightful products for users
Entrepreneurial spirit. You love to build new things and thrive in ambiguity and even failure. You figure out what it takes to drive projects to success.
Excellent communication skills. You collaborate effectively with teams in a fully remote environment and discuss complex topics with technical and non-technical audiences