Who we are:
We are a community of Machine Learning Researchers and Engineers, working to help Twitter leverage ML through a range of systems such as recommendations, safety, abuse, content understanding, ads and more. We operate at scale whilst ensuring fair and ethical use of our models and data.
We work collaboratively, often embedding among product teams, looking to apply the expertise of the individuals to improve our products and unlock new capabilities. We encourage publishing papers, but they are not the end goal, rather a by-product of us doing interesting work - the aim is to make a real-world impact!
The Learning Methods Research Team, part of Cortex Applied Research, enables ML applications across our platform (e.g. recommender system, content / user understanding) to better use Twitter’s sources of data through recent ML methods such as deep learning on graphs or self-supervised learning. In this team, you'll be working closely with leading researchers and will have the opportunity to learn about the current state-of-the-art in ML, contributing to ambitious research projects based on the latest insights.
What you will do:
Apply your research and engineering skills to bring ML research ideas to production, unlock large-scale rapid experimentation, and make sure existing tooling and infrastructure are used to their fullest potential throughout the research lifecycle. You will work closely with research scientists and product teams, learn to deliver ML solutions at scale within the Twitter tech stack, and contribute to the design of new systems and infrastructure to shape how ML is used across the business. Apply your wider experiences to provide perspective, and enable Twitter to benefit more rapidly from fundamental ML research. In addition, you will be directly contributing to research projects, strategic decisions and future roadmaps for products and technologies at Twitter.
Who you are:
You are excited about the challenges of deploying the latest ML technologies at scale and enabling research to go from idea to practical impact. You are passionate about the way we conduct research inspired by our products, our approach to develop state-of-the-art technologies, how we apply them to products, and enjoy the challenge of overcoming real-world constraints. You’re a diligent listener, have the ability to communicate technical issues to non-experts, and can persuade others to follow your recommendations. You have a solid understanding of core ideas in machine learning and software engineering, keep up-to-date with the latest developments in the field and look for ways to apply them in the real world.