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. As a Software Engineer, Product in Ads Infra and Ranking, you will lead complex product engineering projects that make Ads platforms easier to use and integrate. You will build product experiences and supporting services for engineering users, translating platform capabilities into clear workflows and dependable interfaces that support the development, evaluation, and operation of Ads systems.

Qualifications:

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Demonstrated experience driving change within an organization and leading complex technical projects 8+ years of programming experience in a relevant language OR 4+ years experience with a PhD 6+ years relevant experience building large-scale applications or similar experience Experience building developer-facing or technical-user products that simplify complex platform workflows Experience designing product interfaces and supporting APIs for applications integrated with distributed systems or ML platforms Experience in programming languages such as C, C++, Java, Swift, or Kotlin, and scripting languages such as Python, Javascript, or Hack Experience improving product quality through code review, testing, controlled rollout, monitoring, and proactive changes Demonstrated ability to integrate AI tools into product engineering workflows and drive measurable efficiency or quality improvements Experience applying responsible AI practices, including risk assessment and quality and accuracy reviews, when developing or using AI-assisted capabilities Demonstrated ongoing AI skill development, including prompt/context engineering or agent orchestration, and evaluation of emerging technologies for engineering use Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies