Machine Learning, Recommendation Systems (Ads Infra and Ranking)

Job description

Meta's Ads organization builds the systems that help businesses of every size reach the people most likely to care about what they offer. At our core, we're builders who care about shipping real value. Within Ads, the Infra and Ranking organization owns the technical foundation that makes this work at Meta's scale: the ranking models that decide which ad is right for each moment; the retrieval and serving platforms that evaluate enormous candidate sets in milliseconds; and the underlying data, training, and inference infrastructure. All of this is done while maximizing compute efficiency, ensuring reliability and privacy, and using AI to speed up development. Our state-of-the-art research in deep learning architectures, sequence and representation learning, and generative recommenders continuously pushes the boundaries of personalization accuracy. Our innovations in distributed GPU training, model/system co-design, and large-scale low-latency serving let us deploy multi-billion-parameter models that learn continuously from real-time behavior — under strict efficiency, reliability, and privacy constraints. These advances in large-scale ML optimization, ads ranking quality, and personalization infrastructure are crucial to our revenue goals and to innovation across the Meta family of apps. As an ML Software Engineer in Ads Infra and Ranking, you will build production recommendation systems that improve ad relevance through retrieval and ranking. You will own model and software improvements from design and evaluation through rollout, partnering with data and serving engineers to deliver reliable personalization capabilities and measurable improvements.