Machine Learning Engineer - MoPub
Who We Are:
MoPub is the world’s largest mobile application advertising exchange and complete ad serving platform. From individual developers to the largest names in mobile apps and games, MoPub’s customers span the globe with over 30 billion ad requests/day.
What You’ll Do:
We need your help to build and operate mission critical machine learning systems that operate at the center of MoPub’s mobile ad exchange. You will contributed to the entire machine learning lifecycle from building models to running the online distributed systems. This includes writing production code, doing code reviews and operating online online services that make 10s of millions of predictions per second.
- Build and run large-scale distributed systems (500k+ requests per second)
- Work with big data (100s of terabytes and billions of ad requests)
- Create and train machine learning models (using Tensorflow)
- Code primarily in Scala
- Collaborate closely with data scientists, product managers and other software engineers to ship new data driven features for MoPub’s customers.
Who You Are:
You are a backend software engineer who wants to work at the intersection of software engineering and machine learning.
- MS in computer science or equivalent experience.
- Basic understanding of machine learning and/or statistics
- Deep understanding of (one or more of the following): C++, Java, or Scala, plus experience with Python, or R
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, 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.
After you apply, a recruiter may reach out to you for an introductory call.
If your background is a match for the role, you may phone interview with 1-2 people.
If you continue through the process, you will come onsite 1-2 times to interview with a total of 5-10 people.
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