Machine Learning Engineer
Core
Design and implement machine learning models and data pipelines to enhance a programmatic demand-side platform (DSP) for predicting user responses, forecasting bid landscapes, and detecting fraud.
Role type
Machine Learning Engineer
Builds
Production ML models and data pipelines for a programmatic DSP
Domain
Mobile advertising / Programmatic advertising
Deliverable
production ML models
Required skills
Python, SQL, regression, classification, clustering, probability, statistics, data analysis, big data tools (Spark), ML libraries (TensorFlow, PyTorch, Scikit-Learn)
Preferred skills
C++, Rust, online inference systems, gRPC/REST, streaming features (Kafka/Flink), ad-tech (auction dynamics, pacing, fraud signals, creative personalization)
Technologies
Spark, TensorFlow, PyTorch, Scikit-Learn, Kafka, Flink, gRPC, REST
Responsibilities
Develop ML models for user response prediction, bid forecasting, and fraud detection; build and maintain data pipelines; integrate models into production workflows; analyze impact of new data sources; document experiments and outcomes.
Seniority
Mid-level, hands-on IC
