Machine Learning Engineer - Trends & Event Detection

New York, NY

Who We Are:


When an event occurs in the real-world, it often breaks out on Twitter. The Event Detection team builds, scales and maintains the software services that power the discovery of interesting and eventful conversation across the product. We detect and surface what’s happening, contextualizing by finding the most interesting content around events, including Trends, Moments, and Live Videos for users. We are a tightly knit and passionate group that loves working together, and we are looking for exceptional additions to our flock.


What You'll Do:


Events are one of the central use-cases for Twitter and millions of people are informed about their world through our work. The team’s purpose is to automatically detect such Events on Twitter. As an ML engineer on our team, you will apply machine learning and data science techniques to a modeling and relevance problems related to automatic Event detection. You will participate in the engineering life-cycle at Twitter, including building and analyzing datasets, working with offline data pipelines, writing production code, conducting code reviews, and working alongside our systems engineers. Although you will work on cutting-edge problems, please note that this is not a research position. You will work directly with multiple teams across the company who are innovating on the product and refining Twitter to make it the best place to see and talk about what's happening in the world.


Who You Are:


You have a passion for machine learning and improving the ways people consume what’s happening in the world. You are a relevance engineer, applied data scientist or machine-learning engineer who wants to work on exciting algorithmic and infrastructure issues. You are experienced solving large scale relevance problems and comfortable building brand new systems to enable future quality improvements.

  • Knowledgeable in one or more of the following: machine-learning, information retrieval, recommendation systems, social network analysis
  • A strong technical advocate with a background in Java, Scala, or Python. Preferably familiar with Jupyter notebook environments and Spark or pySpark.
  • Passionate about working with large unstructured and structured data sets and developing new approaches to relevance problems.
  • Experienced in collaborating across multiple teams including analytics, product management, and operations.


  • BS, MS, or PhD in computer science or a related quantitative field with 4+ years of software engineering experience
  • Experience with software engineering best practices (e.g. unit testing, code reviews, design documentation)


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 status, 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.

Hiring Process

Step 1

After you apply, a recruiter may reach out to you for an introductory call.

Step 2

If your background is a match for the role, you may phone interview with 1-2 people.

Step 3

If you continue through the process, you will come onsite 1-2 times to interview with a total of 5-10 people.


Personal Information

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U.S.  Equal Employment Opportunity Information  (Completion is Voluntary)

At Twitter, we have a bold aspiration to reach every person on the planet. We believe that goal is more attainable with a team that understands and represents different cultures and backgrounds and we are committed to an inclusive and diverse Twitter.

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Twitter is an equal opportunity employer. We do not 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 legally protected status.

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