Senior Machine Learning Engineer

Job description

Opportunity Description This is an opportunity to join a data-rich technology leader with a combined audience of hundreds of millions of players worldwide. We’re building an Ad Network, leveraging best-in-class industry solutions to unite supply and demand intelligently in underserved digital segments. Our platform is powered by unique access to rich first-party user data derived from our massive owned audience, which gives us an undeniable edge in delivering superior user profiling and higher-performing campaigns. We are initially focused on dominating the high-value iGaming vertical, leveraging this data advantage, with a clear strategic goal of rapidly scaling into other lucrative segments, such as Forex and beyond. You’ll work alongside a leadership team with deep experience from top big tech companies and industry-leading ad platforms, stepping into a pivotal role that offers the chance to define the foundational architecture and deliver immediate, massive impact on a globally scaled product. What You’ll be doing ● Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems. ● Build and refine systems for creative understanding and user behaviour modelling, enabling more accurate and context-aware engagement predictions. ● Responsible for model quality and reliability by monitoring performance, calibrating predictions, and proactively addressing data drift and delayed feedback. ● Clearly communicate complex technical concepts to non-engineering stakeholders in an accessible, outcome-focused way. What we’re looking for ● An MS or PhD in Computer Science, Machine Learning, Statistics, or a related field, or equivalent practical experience. ● Over 3 years of hands-on experience developing and operating large-scale ad delivery and optimization systems. ● Experience working with CTR/CVR modeling, creative or content understanding, or user behavior modeling. ● Strong proficiency in general-purpose programming languages such as Python, Go, Scala, C++, or similar. ● A solid grasp of metric design, experimentation methodologies like A/B testing, and large-scale data processing and analysis