ShopFully is seeking a Senior Machine Learning Engineer to own and extend production ML systems and the backend infrastructure powering 1P, 2P, and 3P audience data across ShopFully and Flipp. This is an engineering-focused role for someone who builds and operates production ML systems end-to-end, not a research-only handoff. You will bring hands-on expertise in statistics, model selection, building, tuning, and experiment design, paired with strong software engineering fundamentals to build scalable pipelines on core tables running into tens of billions of rows. If you are passionate about MLOps, scalable feature engineering, and shipping production ML systems that drive measurable business impact, this role is for you!

What you will do: - End-to-End ML Systems Ownership: Design, build, deploy, and monitor production ML models and pipelines—such as the IAB Segmentation Model, Retailer & Category Affinity Segments, and Custom Segment Toolkits. - Feature & Data Engineering at Scale: Build and maintain high-volume feature engineering and data pipelines using Spark, Databricks, Python, and SQL, working with core tables containing tens of billions of rows. - MLOps & Model Lifecycle Management: Implement robust MLOps practices, including model registries, offline/online evaluation, experiment tracking (MLflow or equivalent), and monitoring for data/model drift and quality. - Audience Platform Integration: Collaborate on the platform side (Audience API, User Profile API, Kafka Topics, and activation integrations like DV360, Braze, and TTD) to ensure models seamlessly integrate

ShopFully is seeking a Senior Machine Learning Engineer to own and extend production ML systems and the backend infrastructure powering 1P, 2P, and 3P audience data across ShopFully and Flipp. This is an engineering-focused role for someone who builds and operates production ML systems end-to-end, not a research-only handoff. You will bring hands-on expertise in statistics, model selection, building, tuning, and experiment design, paired with strong software engineering fundamentals to build scalable pipelines on core tables running into tens of billions of rows. If you are passionate about MLOps, scalable feature engineering, and shipping production ML systems that drive measurable business impact, this role is for you!

What you will do: - End-to-End ML Systems Ownership: Design, build, deploy, and monitor production ML models and pipelines—such as the IAB Segmentation Model, Retailer & Category Affinity Segments, and Custom Segment Toolkits. - Feature & Data Engineering at Scale: Build and maintain high-volume feature engineering and data pipelines using Spark, Databricks, Python, and SQL, working with core tables containing tens of billions of rows. - MLOps & Model Lifecycle Management: Implement robust MLOps practices, including model registries, offline/online evaluation, experiment tracking (MLflow or equivalent), and monitoring for data/model drift and quality. - Audience Platform Integration: Collaborate on the platform side (Audience API, User Profile API, Kafka Topics, and activation integrations like DV360, Braze, and TTD) to ensure models seamlessly integrate