Job Description

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.

Responsibilities

Manage multiple teams of ML engineers and technical leaders delivering on large-scale systems infrastructure projects with significant organizational dependencies

• Actively shape and influence the technical strategy and roadmap for systems-level initiatives, translating long-term goals into executable plans
• Drive consistent execution against engineering strategy by proactively identifying and resolving blockers related to vision, technical direction, or team dynamics
• Maintain technical engagement across teams by evaluating architectural decisions, system design quality, and codebase health using available tooling and direct contribution
• Build and grow the team by sourcing and closing candidates, developing engineering leaders, and ensuring smooth onboarding for new team members
• Invest strategically in engineering craft by improving team workflows, tooling, and processes that raise the quality and reliability of systems over time
• Foster a team culture of accountability, continuous improvement, and open communication where engineers feel empowered to raise concerns and take ownership
• Partner substantively with product, design, data science, and infrastructure stakeholders to align systems investments with broader business and product goals
• Communicate technical context, risks, and progress effectively to engineering leadership and cross-functional partners at all levels of the organization
• Hold engineering leaders accountable for performance management, upward feedback, and maintaining a high bar for technical and operational excellence

Qualifications

7+ years of software engineering experience, including experience in ML technical leadership or ML engineering management

• 4+ years of engineering management experience, including directly managing engineers and leading teams through complex technical projects
• Experience managing other engineering managers or technical leads and developing them into effective leaders
• Experience driving technical strategy and roadmap definition for large-scale systems with multiple levels of organizational dependencies
• Experience recruiting, retaining, and developing engineering talent in a fast-moving technical environment Experience leading teams in a high-growth or ambiguous product or infrastructure domain where technical direction required active definition
• Experience using feature flagging and staged rollout frameworks to manage risk and drive iterative delivery across multiple teams
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to improve engineering efficiency through investment in tooling, workflows, and codebase health at an organizational level
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies