Senior Machine Learning Engineer

Responsibilities: Design, build, and deploy large-scale ML systems for ad ranking, click-through and conversion prediction, bid optimization, and next-best-action recommendation Build and operate production ML pipelines—feature engineering, distributed training, deployment, retraining, and monitoring—processing billions of events and serving predictions with low latency Leverage cross-product data assets to enable real-time decisioning using a broad feature set Optimize training and inference for compute efficiency, latency, and cost across distributed systems Collaborate with Data Science, Data Engineering, and product teams to ship models that affect key business metrics and run online experiments Stay current with applied ML research and introduce new techniques to advertising, ranking, and audience modeling

Key requirements: 8+ years of production ML systems experience in AdTech, recommender systems, search/ranking, or real-time bidding Strong software engineering fundamentals (data structures, algorithms, design) and Python (plus Java/Scala/C++ a plus) Hands-on with ML frameworks (PyTorch, TensorFlow, or JAX) and distributed systems (Spark, Beam/Dataflow, Flink) Experience building robust ML pipelines (feature stores, data versioning, model monitoring, retraining) track record of shipping models that improve product metrics (CTR, CVR, ROAS) Master’s or Ph.D. in CS, ML, or related field, or equivalent practical experience collaboration across cross-functional teams data-driven decision making ability to run online experiments and iterate quickly Python Java/Scala/C++ PyTorch, TensorFlow, or JAX