Job description

Who we are

Are you interested in helping build a new Twitter experience? Our team is working to connect users to content based on their interests and intent in addition to who they follow. We do this working within the Twitter Search stack -- it is the search engine for Twitter, and the way to find the most relevant and engaging content for any topic or interest. Twitter Search is a fast growing search engine, which our users rely on to find public accounts and conversations. The product requires building a high quality experience for a wide range of queries in real time. Often this means our systems need to understand the intent behind user queries, be able to match large streams of content with that intent, which are then ranked and displayed. We build technology to enable us to deliver this at scale. We have a mix of Systems and Applied ML engineers who work on the user facing product, as well as the models that improve the quality of the product.

What you will do

Apply your research expertise to help direct our product modeling efforts, focusing on using creative data-driven ML approaches to solving open-ended product questions. Help us develop new solutions and unlock new directions, as well as analyze and improve the systems we already have. You’ll work closely with ML engineers and data scientists and mentor them on modern approaches to using ML for solving product challenges at Twitter’s scale. You will be collaborating on strategic decisions and future roadmaps for Machine Learning driven products and technologies at Twitter. You are a key member of the Cortex Boston Product Modeling team, which consists of authorities in ML, data science, and software engineering. Your impact will directly affect millions of Twitter users around the globe.