At Twitter, we serve billions of ad impressions and generate millions of dollars in revenue per day. For every ad shown on Twitter, our machine learning systems evaluate, in real-time, millions of ad candidates behind the scenes to find the best one. We are looking for talented individuals to further develop this state-of-the-art system, working as part of the machine learning engineering and data science team. We create aha! moments for our users & advertisers and add huge value to Twitter’s business & revenue.

You will be involved in the full array of modern applied machine learning work, including ideation, experimentation, implementation, and maintenance. This includes work across our ads stack on predictive modeling, improving the way the system explores new traffic, mitigating effects of selection bias, effective budget pacing, efficient AB testing, accurate candidate ranking, visualizations, and more. We’re looking for a key individual contributor to drive our advertising products forward. 

Your team will empower you with the autonomy to make good product decisions and discover/understand the software and product stack. You’ll own significant projects end-to-end. The small teams of talented, passionate people in which you’ll work will include engineers and data scientists from across the revenue engineering organization. 

This position is available in: San Francisco, CA, Remote US, Los Angeles, CA; Sunnyvale, CA; Boulder, CO; Washington, D.C.; Chicago, IL; Cambridge, MA; New York, NY; Seattle, WA 

Who You Are:

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

• Stay abreast of and leverage recent advances in machine learning.

• Deep understanding of foundational math associated with machine learning such as linear algebra, numerical optimization, probabilistic models, and statistics. 

Minimum Qualifications: 

• 4+ years of industry experience doing Applied Machine Learning

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

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

• Passionate about working with large unique data sets

• Comfortable conducting design and code reviews

Preferred Qualifications:

• Bachelor’s, Master’s or PhD degree in Computer Science, Mathematics or related quantitative field

• Industry experience with online advertising and/or large-scale distributed systems

All your information will be kept confidential according to EEO guidelines.

After you complete your application and click submit, you will receive an on-screen success message confirming your application has been submitted. Within 5-10 minutes of submission, you will receive an email from [email protected] confirming your application has been submitted. If you do not receive a confirmation email, check your spam or trash folder. We strongly recommend you apply with a personal email versus your school email.