We're looking for a talented and passionate Staff Machine Learning Engineer to join Wildlife's DSP team.
The DSP is building a brand new commercial product that helps mobile-first companies scale distribution while maintaining a target return. By integrating post-installation data from its clients, the DSP is able to optimize in real-time the ad spend that goes to different campaigns across hundreds of mobile advertising channels. We leverage information from 2 billion device profiles and handle 1,000,000 bid requests per second with a single digit ms response time. We train several ML models and serve them online to directly control millions of dollars of ad spend.
We'll need you to familiarize yourself with the domain and become a reference for technical implementation. To achieve this, we expect you to work on tasks such as: scaling both our current and new ML implementations to deal with PBs of data, optimizing for time and computational efficiency, helping create new data and model training pipelines to tackle novel problematics, and designing and developing tools and frameworks to help the Data Science and Data Engineering teams accelerate their development and experimentation cycle, adopting MLOps best practices.
Since we are always looking for new tools and technologies to better solve our problems, we value professionals that like to learn new things, are autonomous and proactive to bring and implement their ideas.
Wildlife is one of the leading mobile game developers and publishers in the world. We have released more than 60 titles, reaching billions of people around the globe. Today, we have offices in Brazil, Argentina, Ireland, and the United States. Here, we create games that will excite, intrigue, and engage our players for years to come!
Wildlife is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, colour, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.
We're committed to providing accommodations for candidates with disabilities in our recruiting process. If you need any assistance, please let us know at email@example.com.