Machine Learning Engineer

Remerge helps leading mobile app marketers increase revenue and retention by activating, re-engaging and retaining high-value users through programmatic in-app ads. Founded in 2014, Remerge has established itself as a leading app retargeting player globally, with offices spanning Berlin, New York, Singapore, Seoul and Tokyo. Our international team of experts has contributed to the growth of hundreds of apps across all major verticals, including gaming, on-demand delivery, e-commerce, and finance. We are looking for a pragmatic, curious, and AI-fluent Machine Learning Engineer to join our Performance team. Beyond core ML, our work touches a range of disciplines like reinforcement learning, control engineering, mathematical optimization, and causal inference, to name a few. If you already have depth in any of these, great; if not, there's plenty of interesting territory to explore alongside the core ML work. About the Team The Performance team is the brain behind our bidding infrastructure. We handle the core algorithms responsible for maximizing ad performance and optimizing return on ad spend (ROAS) within the strict parameters set by our advertisers. We run a hybrid setup; training in the cloud and inference on our own hardware. That mix gives us the freedom to push the boundaries of high-throughput ML, while keeping us honest about the cost and scale trade-offs of doing so. We have a pragmatic view about what 'ML' means here; feature pipelines, online serving, and monitoring are part of the job, not someone else's problem. In this role you will... Develop & Scale ML Models: Build, train, and deploy high-performance machine learning prediction models optimized for real-time adtech environments. Own the Full ML Path: Take models from raw data and feature definitions through training, evaluation, and online serving. Feature engineering and online/offline consistency matter as much as modelling skill. Optimize the Bidding Engine: Design and refine complex bidding algo