Senior Machine Learning Systems Engineer, Ads ML Experience Platform

Role overview A senior engineering role focused on the machine learning systems that power the experience layer of a large-scale advertising platform. The position sits at the intersection of applied ML and platform engineering, working on the infrastructure and services that make ad ranking, retrieval, and personalization fast, reliable, and observable in production.

Responsibilities - Design and evolve the ML platform that serves ads at scale, balancing latency, throughput, and cost. - Build and operate distributed training and inference pipelines for ranking and personalization models. - Partner with modeling, ads, and product teams to translate experimentation into production-ready systems. - Improve model serving reliability through better monitoring, evaluation, and rollout tooling. - Contribute to technical direction on model lifecycle, feature platforms, and online/offline consistency.

Requirements - Several years of experience building and operating large-scale ML or ads systems in production. - Strong background in distributed systems, data pipelines, and high-throughput serving infrastructure. - Proficiency in Python and at least one systems language such as C++, Go, or Java. - Familiarity with ML frameworks and the practical tradeoffs of training, deploying, and monitoring models. - Comfort working across ML, infrastructure, and product boundaries.

Nice to have - Experience with ads ranking, retrieval, or real-time personalization stacks. - Background contributing to internal ML platforms used by other engineering teams.