Staff Machine Learning Engineer, Ads Optimization

Job Description

“The front page of the internet," Reddit brings over 430 million people together each month through their common interests, inviting them to share, vote, comment, and create across thousands of communities.
Reddit is the 4th largest website on the internet, generating billions of events and terabytes of data every day. The Ads Optimization and Modeling team uses those events to generate machine learning systems that supercharge the performance of our ads platform.
We are a team of engineers and data scientists dedicated to using machine learning to improve Reddit’s ads experience. The majority of Reddit’s revenue passes through our systems, and every improvement to our predictions translates into big wins for our business. You’ll own full-stack ML projects from ideation to production to turn data into products that millions of people love.
You’ll use your ads machine learning experience to set long-term ML strategy, charting a path through model architecture, feature generation, and evaluation and experimentation. You’ll own all modeling aspects of our mission critical clickthrough rate and conversion rate models. You’ll help develop an ML roadmap, as well as guide other engineers through executing it.

Responsibilities:

• Adapt the ads industry’s machine learning best practices to Reddit’s unique platform and user base.
• Lead analysis and implementation of features and signals.
• Write production code to ship your model to millions of users.
• Participate in the full software development cycle: design, develop, QA, deploy, experiment, and analyze.
• Collaborate across disciplines to find technical solutions to complex challenges.

Requirements:

• 5+ years as a Machine Learning Scientist or Machine Learning Engineer, 2+ of which were spent in an Ads Machine Learning context
• Up to speed on industry best practices in ads machine learning.
• Strong communication and collaboration skills
• Software Engineering practices and the ability to write performant production-quality code
• Comfortable with distributed learning, big data and large-scale systems
• Master’s or PhD in Statistics, Machine Learning, Mathematics, Computer Science, or related field