Software Engineer, Machine Learning - Ads Products

Meta•Menlo Park, CA

1d•$183,997 - $257,000

About The Position

Meta's Ads organization builds systems that help businesses reach people likely to care about their offerings. The organization owns advertiser-facing products and systems, including campaign and optimization products, business experiences for planning and managing advertising, signals, attribution and measurement, payments and financial systems, and integrity work. As a Software Engineer, Machine Learning in Ads Products, you will lead complex engineering projects that turn machine learning 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.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
8+ years of programming experience in a relevant language, or 4+ years of 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.

Nice To Haves

Experience with privacy-preserving measurement and modeling under signal loss, such as aggregated or delayed conversion signals.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Demonstrated ongoing AI skill development, such as prompt/context engineering and agent orchestration, and staying current with emerging AI technologies.

Responsibilities

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.