机器学习工程师 — 推广交付

We are seeking a Machine Learning Engineer to join our Campaign Delivery team. This role is central to designing and deploying the predictive models and recommendation systems that power how we match campaigns to the right users at the right time. You’ll partner closely with Data Engineers, Product Managers, and Campaign Operations to build ML solutions that directly improve delivery performance, advertiser outcomes, and platform efficiency.

5+ years of experience in machine learning engineering or applied data science, with a strong track record of shipping models to production environments. Strong proficiency in Python and hands-on experience with tabular ML frameworks such as scikit-learn, XGBoost, and/or LightGBM. Demonstrated experience building recommendation systems, ranking models, click-through rate (CTR) prediction, conversion rate models, or similar predictive systems at scale. Experience building classification or anomaly detection models—ideally in fraud detection, traffic quality, conversion validation, or similar trust-and-safety domains. Experience with feature engineering, feature stores, and data pipelines using tools like Spark, Airflow, or dbt; familiarity with experiment tracking and model lifecycle management tools such as MLflow. Solid understanding of model evaluation methodology, experimentation design, and A/B testing with statistical rigor. Experience deploying and serving models in production via REST APIs, containerized services, or serverless architectures (AWS SageMaker, Lambda, ECS, or similar). Familiarity with cloud infrastructure (AWS strongly preferred) and data warehouses (Redshift, Snowflake, or similar). Strong communication skills with the ability to translate complex technical concepts into business narratives, in both spoken and written English.