Staff Machine Learning Engineer - User Signals

  • Full-time

Company Description

Twitter serves the public conversation by encouraging people all over the world to connect, learn, debate, and solve problems together. We believe conversation can change the world, and that's why Tweeps (that's what we call Twitter employees) come to work every day.

Who We Are: The User 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.

What We Do: We seek to improve Twitter’s understanding of its users, in order to provide the best, personalized experience. We create representations of users that incorporate interests, behaviors, attributes, and geospatial context. We develop machine learning models to advance Twitter’s capabilities in these areas, and seek to leverage state-of-the-art techniques, including large scale graph learning.

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

Job Description

What you will do: Work together with a team of Software Engineers, Machine Learning Engineers, and Data Scientists to design, develop, and own deep learning models and critical infrastructure that serves user representational data. This includes driving the creation of time-critical, scalable systems for new models, as well as enhancing and improving current ones. 

You will help the team move fast and stay nimble, while collaborating with product teams to help integrate our systems, and be the authority on all aspects of our models and software. As a member of the team, you can also expect to influence the team's roadmap and help us shape our technical strategy to meet key customer needs.

Qualifications

  • MS or PhD in Computer Science or Machine Learning related degree, or other quantitative discipline

  • 7+ years of applied machine learning experience

  • Demonstrated experience tech-leading machine learning teams, and collaborating with cross-functional partners such as Product, Design, and Research

  • Fluent in one or more languages including Java, Scala, C++, Python

  • Familiar with software development life cycle and best practices.

  • Experience with relational, non-relational, and/or distributed data sources a strong plus

  • Experience in social media, user engagement/representational modeling a strong plus

Additional Information

Culture:

We care about making work happy and productive for everyone, with the option to work remotely, in office or both, wellness benefits, regular #NoMeetingThursdays, #FocusTuesdays, and 20 weeks of parental leave. 

We love sharing knowledge and ideas. Within our team, we have regular learning seminars. We regularly get together with the other Twitter engineering teams for tech talks. And there are many study groups you can join, the most recent being for Machine Learning.

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.

  • Collaboration - There’s that saying, “If you want to go fast, go alone. If you want to go far, go together.” We want to go far.

  • Variety - We encourage team rotations that allow you to work with and learn from other teams at Twitter.

Job opportunities should be equal. We don't discriminate. Period. In legal terms, that means: Twitter is an equal opportunity employer and doesn’t discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any other legally protected status.

San Francisco applicants: In response to the San Francisco Fair Chance Ordinance, we’d like to mention that we consider qualified applicants with arrest and conviction records.

Privacy Policy