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

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 technical leader in Ads Products, you will shape the long-term engineering direction of ML-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.

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.

Qualifications

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