Software Engineer, Machine Learning (Technical Leadership) - Ads Products

Meta•Menlo Park, CA

1d•$219,000 - $301,000

About The Position

Meta's Ads organization builds systems that help businesses reach people likely to care about their offerings. It develops 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 capabilities. As a technical leader in Ads Products, you will shape the long-term engineering direction of machine-learning-powered advertiser products. You will connect campaign optimization and advertiser-experience opportunities with the models, data, and product systems needed to deliver them, guiding cross-team engineering efforts from technical strategy through measurable advertiser impact.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
12+ years of programming experience in a relevant language, or 8+ years of experience with a PhD.
Proven track record of planning a multi-year roadmap in which short-term projects ladder to the long-term mission.
Experience driving large cross-functional or industry-wide engineering efforts.
Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.
Experience communicating and working across functions to drive solutions.
Experience mentoring or influencing executive stakeholders across organizations.

Nice To Haves

Publications, patents, or open-source contributions that shaped the recommendations or ranking field.
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 or agent orchestration, and staying current with emerging AI technologies.

Responsibilities

Define a multi-year technical roadmap for ML-powered campaign optimization or advertiser experiences, connecting near-term product work to long-term advertiser value.
Guide model and software architecture across the data, services, and application integrations needed for dependable ML products.
Drive cross-functional engineering efforts with product, data science, and engineering partners to move capabilities from evaluation to production impact.
Use data and experimentation to evaluate model and product decisions and communicate technical trade-offs to engineering and executive stakeholders.
Mentor and influence engineers and technical leaders across teams, improving model evaluation, engineering quality, and reliable product delivery.