At Twitter, their mission is to instantly connect users to the information most meaningful to them. Realizing this involves work in areas such as machine learning, applied data science, recommendation systems, information retrieval systems, natural language processing, large graph analysis, spam, etc.
The team’s mission is to show users the content they care about. They build relevance and machine learning models and systems to power the core of the Twitter product. Every time users see new tweets they evaluate candidates from nearly half a billion daily tweets to select, organize and deliver the best timeline. The recent products and technologies built by their team have shown consistent results in driving retention and are some of the largest contributors to engagements on the platform.
What You’ll Do
Although you will work on cutting-edge problems, this position is not a research position. You will participate in the engineering life-cycle at Twitter, including designing distributed systems, writing production code, conducting code reviews and working alongside their infrastructure and reliability teams. You’ll apply data science, machine learning and/or graph analysis techniques to a variety of modeling and relevance problems involving users, their relationships, their tweets, and their interests.
Who You Are
You’re a relevance engineer, applied data scientist or machine-learning engineer who wants to work on exciting algorithmic and deep infrastructure issues. You’re experienced solving large scale relevance problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements.
Requirements
They are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. They do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.
