Senior Machine Learning Engineer, Ads Optimization
- New York, NY
“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.
The Ads Optimization team at Reddit uses machine learning to supercharge the performance of our ad platform. Our work touches almost every dollar spent on Reddit, and we own all of Reddit’s Ads Machine Learning systems, including clickthrough rate prediction, ad targeting, inventory maximization, and more.
How You'll Have Impact:
We are a team of builders that value impact and personal growth, and we’re looking for ML Engineers/Scientists to help us bring community and belonging to everyone. Reddit is the 6th largest website on the internet, generating billions of events and terabytes of data every day. You’ll own full-stack ML projects from ideation to production to turn this data into products that millions of people love.
What You’ll Do:
You will be in the unique position of directly improving Reddit’s revenue and ad efficiency using Machine Learning. As a full-stack ML engineer, you’ll own the entire ML system lifecycle from conception in a notebook all the way to at-scale deployment on our Cloud-based clusters. You’ll also build infrastructure to help keep pace with one of the fastest-growing ML platforms in the world.
- Apply Machine Learning / Artificial Intelligence to optimize ad platform efficiency.
- Dig into Reddit’s unique product challenges, and go beyond generic out-of-the-box algorithms.
- Analyze and implement features, and train Machine Learning models on large-scale data.
- Collaborate across disciplines to find technical solutions to complex challenges.
- 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.
- 1+ years as a Machine Learning Scientist, Machine Learning Engineer, or Data Scientist
- An ML generalist experienced in building ML pipelines.
- A theoretical understanding of ML concepts and techniques. Knowledge of Statistics is a plus.
- Software Engineering practices and the ability to write performant production-quality code.
- Comfortable with distributed learning, big data and large-scale systems
- A degree in Statistics, Machine Learning, Mathematics, Computer Science, or related field
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