Machine Learning Engineer focused on MLOps, deployment, and performance optimization for AI-driven game concepts, bridging research and production for cloud and edge environments.

Machine Learning Engineer at Netflix focused on Ads Inventory Management & Forecasting. The role involves building end-to-end ML model deployment and inference infrastructure for low-latency real-time ad systems, handling large data volumes with Spark, and productionizing predictive models for campaign effectiveness forecasting. It also includes building scalable simulation solutions for inventory scenarios and collaborating with cross-functional teams.

Netflix is hiring Machine Learning Engineers for their Ads Platform Engineering teams. The role involves building and deploying ML models for low-latency real-time ad systems, focusing on areas like inventory forecasting, ad serving, programmatic interfaces, member experience, and audience targeting. Responsibilities include developing and productionizing predictive models for campaign effectiveness, yield optimization, bid ranking, and dynamic allocation, as well as building scalable simulation solutions. Experience with big data tools like Spark and proficiency in languages like Java, C++, Python, or Scala are required.

Netflix is seeking a Software Engineer for their Machine Learning Platform team to develop and expand their model serving systems, focusing on infrastructure for LLMs and other large foundation models. The role involves building scalable, robust systems for online ML model inference, optimizing for latency and cost, and ensuring high availability and performance. This is a highly cross-functional role partnering with various engineering and data science teams.