Twitter is what’s happening and what people are talking about right now. For us, life's not about a job, it's about purpose. We believe real change starts with conversation. Here, your voice matters. Come as you are and together we'll do what's right (not what's easy) to serve the public conversation.
This team is focussed on helping consumers discover content that is interesting and relevant to them. We build large scale personalized recommendation engines utilizing different signals such as social network, user activity, and geolocation.
As a part of this team, you will get to solve large scale relevance and ranking problems and improve product quality. You will train new ML models, build data pipelines, do feature engineering, and perform a/b testing to launch and enable product improvements.
You have a passion for machine learning and improving the ways people consume the world, live. You’re a relevance engineer, applied data scientist or machine-learning engineer who wants to solve customer problems using Machine Learning. You’re experienced solving large scale relevance & ranking problems and comfortable building pipelines and iterating on ML models to enable future quality improvements.
Knowledgeable in one or more of the following: machine learning, information retrieval, recommendation systems, social network analysis
Designed and evaluated approaches for handling high-volume real-time data streams.
Machine learning practitioner with a background in Java, Scala, or Python.
Comfortable conducting design and code reviews.
Effective in communicating with different functions (product, user research, design, and engineering)
BS, MS, or Ph.D. in Computer Science with 4+ years of related or equivalent experience.
Knowledge of Machine Learning techniques and Recommendation systems.
A few other things we value:
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, ethnicity, color, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran, genetic information, marital status or any other legally protected status.
San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records