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.
Who We Are: The Topic Signals team is part of Cortex, the central machine learning organization at Twitter. Cortex’s mission is to empower internal teams to efficiently leverage machine learning by providing platform, modeling, and research expertise while advancing the ML technologies within Twitter.
We tackle Twitter-specific challenges in building topical models for our content. These include tweets, spaces, and other forms of user-generated content on our platform. We apply and advance state-of-the-art machine learning techniques to invent new models and systems that can be used to help us understand the semantics of content, and ultimately improve various Twitter experiences for our customers.
We operate at scale whilst ensuring fair and ethical use of our models and data.
What you will do: Apply your NLP expertise to propose and develop models and solutions that improve the topical understanding of tweets and text. Devise models and algorithms and guide engineering to develop scalable solutions that can work in real-time with large amounts of data. Help us develop novel solutions, and unlock new directions in both the methods we use and the application of our team's work.
You will collaborate with product teams to help them apply NLP and our topic models in the best possible way for their applications and use cases. As the authority on topic modeling and content understanding, you will be able to influence the team’s roadmap and help product teams seek out new opportunities to leverage our models and solutions.
You will also be engaging with the research community via publications and conferences. Twitter, and our team, are suitably positioned to be thought leaders in the space of topic modeling and social media content understanding.
Who you are: You have sound knowledge of state-of-the-art NLP models (in particular deep learning models) and are capable of applying them to real-world problems. You are comfortable with building production-grade software systems, and are up-to-date with software engineering best practices. You are keen to continue learning and developing your expertise in machine learning.
Masters degree or Ph.D. in Computer Science or Machine Learning related degree; or equivalent work experience in the field
3+ years NLP applied research experience, preferably experience applying NLP research to real-world problems in the industry
2+ years of experience building production NLP models, and deploying them to solve inference challenges at scale
Good theoretical grounding in core machine learning concepts and techniques
Ability to perform comprehensive literature reviews and provide critical feedback on state-of-the-art solutions and how they may fit different operating constraints
Experience with a number of ML techniques and frameworks, e.g., data discretization, normalization, sampling, linear regression, decision trees, SVMs, deep neural networks, etc.
Familiarity with one or more deep learning software frameworks such as Tensorflow, PyTorch
Preferably publications in top conferences/journals including ACL, EMNLP, and NAACL
A few other things we value:
Challenge - We solve some of the industry’s hardest problems. Come to be challenged, learn, and thrive as an engineer.
Diversity - Diversity makes us a better organization and team. We value diverse backgrounds, ideas, and experiences.
Work, Life, Balance - We work hard, but we believe with hard work should come balance.