“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 Core Machine Learning team at Reddit is a 10x team that owns recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth and Ads. 

How You'll Have Impact:

As the 6th largest site on the internet, Reddit generates billions of events and terabytes of data in a day. You will own projects from ideation to production instead of being stuck making small incremental gains on enterprise systems. We are looking for the best and the brightest Machine Learning Engineers/Scientists to join us in solving hard problems in order to create things that millions of users will love. We are a team of builders that value impact, personal growth, openness and kindness.

What You’ll Do

You will be in the unique position to revolutionize personalized video content discovery using Machine Learning techniques including Deep Learning, Natural Language Processing, Recommendation Systems, Representation Learning and Computer Vision.

Responsibilities:

• Apply Machine Learning / Artificial Intelligence to personalization, discovery and recommendation problems in the video-ranking space
• Build Machine Learning models from Petabytes of data using the Google Cloud Platform.

• Design Machine Learning solutions for Reddit’s unique product challenges.
• Extract intelligence from data by applying analysis and feature-engineering techniques.
• Iterate on Machine Learning products based on the feedback from A/B experiments and product managers.
• Deploy your model to serve millions of users.
• Participate in the full software development cycle: design, develop, QA, deploy, experiment, and analyze.

Requirements:

• 3+ years of work experience as a Machine Learning Scientist or Engineer; or 2+ years of work experience plus a degree in Machine Learning, Data Science or Statistics.
• Solid theoretical knowledge of Machine Learning and Statistical concepts, including Deep Learning, common Neural Network architectures as well as performance tradeoffs.
• Familiarity with at least 2 of: Tensorflow, Keras, PyTorch and Sklearn
• Comfortable with distributed learning, big data (Petabyte scale) and data-intensive systems
• The ability to extract insight from data
• Proficient in Python and SQL
• Passionate about building delightful products for users
• Strong communication and team-work skills

Pluses:

• Work experience in Recommendation Systems and Feeds-ranking a very strong plus
• Knowledge of Natural Language Processing, Reinforcement Learning or Self Learning
• The ability to understand and implement publications in the fields of Artificial Intelligence/Machine Learning
• Exposure to data-intensive systems as well as writing production-quality software
• Familiarity with Google Cloud pipelines, Go and Scala