The Position

Who We Are: The Interest Foundations team is part of Discovery & Connect, one of the largest consumer organizations at Twitter. The team’s mission is to leverage machine learning to properly understand the content we have on Twitter, and exploit this understanding to support applications including personalized recommendations.

We tackle Twitter-specific challenges in sifting through content on Twitter, and recommending the best content to our users based on their needs and preferences. 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 what our customers care about, and ultimately improve their experience on Twitter.

We operate at scale whilst ensuring fair and ethical use of our models and data.

What you will do: Apply your recommendations and ranking expertise to propose and develop models and solutions that will improve the personalized content that users see on Twitter. 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 our recommendation systems in the best possible way for their applications and use cases. As the authority on personalization and recommendation, 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 social media content understanding and personalization.

Who you are: You have sound knowledge of state-of-the-art recommendation approaches and techniques, 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.

Qualifications

• Masters degree or Ph.D. in Computer Science or Machine Learning related degree; or equivalent work experience in the field
• 3+ years applied research experience, preferably experience applying personalization/recommendations research to real-world problems in the industry
• 2+ years of experience building production recommendations 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 SIGIR, and ACL.

Company Description

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.