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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. We own the advertiser-facing side of that work, end to end: the campaign and optimization products that drive advertiser results; the business experiences where advertisers plan, create, and manage their work, from a first boosted post to a global agency's workflow; the signals, attribution, and measurement that prove what their advertising delivered; and the payments and financial systems the money moves through, along with the integrity work that keeps them trusted. AI is changing all of it - what we build for advertisers and how we build it - and ours is the org where advertiser value is won or lost. As a Software Engineer, Machine Learning in Ads Products, you will lead complex engineering projects that turn ML capabilities into useful advertiser products. You will develop and integrate models for campaign optimization and advertiser experiences, partnering with product, data science, and engineering teams to define success, evaluate improvements, and deliver reliable capabilities that help businesses achieve better advertising results.
Define and deliver ML-powered product capabilities for campaign optimization or advertiser experiences, from technical design through launch and iteration. Translate advertiser and product needs into model objectives, evaluation methods, and maintainable production software. Use data and analysis to diagnose model and product behavior, compare technical approaches, and guide engineering decisions. Partner with product, data science, and engineering teams to design experiments and assess advertiser outcomes. Lead cross-functional execution across model, data, service, and product integration dependencies for complex projects. Improve model and product quality through testing, rollout controls, monitoring, and production feedback. Mentor engineers in ML product design, evaluation, and reliable delivery. Help teammates ramp up across the model, data, service, and product codebases.
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of programming experience in a relevant language OR 4+ years experience with a PhD Demonstrated experience driving change within an organization and leading complex technical projects Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Experience with privacy-preserving measurement and modeling under signal loss (e.g. aggregated/delayed conversion signals) 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
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