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. We build features that help make our infrastructure more efficient and scalable to handle growing traffic on the platform.
What You’ll Do:
As a part of MoPub’s Data team, you will join a small and passionate engineering team working on our MoPub data pipeline, machine learning models, and various systems that use data to make better decisions for our customers. You will work closely with data scientists, product managers, data analysts and software engineers to design, develop, measure and ship new data driven features that generate significant new revenue for MoPub.
- Improve MoPub auction dynamics to help maximize publisher value while providing highly valuable solutions to advertisers.
- Design models, extract features and run experiments to improve the efficiency of matching ad requests with auction participants.
- Build systems and design metrics to A/B test new features and measure product impact.
Who You Are:
- You want to learn how the world’s leading Ad Exchange works
- You seek complex problems, learn quickly, and persist towards optimal solutions
- You understand core Computer Science concepts such as common data structures and algorithms
- You have experience at scale
- Experience building models, engineering features, and using data intelligently to optimize product performance.
- Experience with Hadoop or other MapReduce-based architectures
- Experience analyzing large data volumes (10-100s of TBs) in a modern distributed systems environment
- Ability to thrive in an unstructured environment, working autonomously on a strong team to find opportunity and deliver business impact
- Deep understanding of (one or more of the following): C++, Java, or Scala, plus experience with Python, or R
- Past experience in adtech
- Experience in production stacks involving machine learning, AB testing, or control systems
- PhD or MS in computer science, machine learning, or statistics
- Active contributor to a well-known open source project
- Interesting side projects or Kaggle competition results
- Entrepreneurial mindset
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.
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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