Staff Machine Learning Engineer - Recommendations Platform

Twitter San Francisco , CA 94118

Posted 2 months ago

Who We Are:

Recos Platform team builds recommendations platforms such as candidate generation and feature generation engines for product teams. The unrivaled challenges that we face at Twitter are both the data scale and the real-time nature of the product. How do you find the most meaningful content among hundreds of millions of new tweets for hundreds of millions of users every day at Twitter? We build large scale personalized recommendation engines utilizing different kinds of signals such as social network, user activity, and geolocation. Most of our work is about recommendation systems, machine learning, graph algorithms, distributed systems, and social graph analysis.

What You'll Do:

Apply your engineering skills to either improve existing recommendation systems, unlock new directions or provide entirely new ML solutions in recommendation systems within Twitter. You will work closely with live production systems and product teams, and deliver ML solutions at scale within the Twitter tech stack.

Who you are:

A machine learning software engineer with a passion for working on exciting algorithmic and deep infrastructure issues in ML environments.

  • Thrive on working in concert with other smart people, including from distributed offices.

  • Communicate fluidly, at the level of your audience, and seek to understand and be understood.

  • Have the ability to take on complex problems, learn quickly, iterate, and persist towards a good solution.

  • Take pride in polishing and supporting our products.

  • Work hand-in-hand with modeling engineers and data scientists, and your passion is to enable them with better infrastructure.


BS, MS or PhD in Computer Science with 5+ years experience or equivalent experience.

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

  • Experience with Hadoop, Pig or other MapReduce-based architectures

  • Knowledgeable of core CS concepts such as common data structures and algorithms

  • Comfortable conducting design and code reviews

We are committed to an inclusive and diverse Twitter. 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.

San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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Staff Machine Learning Engineer - Recommendations Platform