Software Engineering Manager, Ads Infra Ranking

Meta•Sunnyvale, 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. The Ads Infra and Ranking organization owns the technical foundation for ad ranking models, retrieval and serving platforms, and the data, training, and inference infrastructure that supports them at Meta's scale. The organization focuses on compute efficiency, reliability, privacy, and using AI to accelerate development. The Software Engineering Manager will lead multiple teams of ML engineers and technical leaders delivering large-scale systems infrastructure projects. The role shapes technical strategy and roadmaps, sustains technical engagement across teams, develops engineering leaders, recruits and grows talent, improves engineering practices, and partners with cross-functional stakeholders to align systems investments with business and product goals.

Requirements

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.

Nice To Haves

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, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Demonstrated ability to improve engineering efficiency through organizational investment in tooling, workflows, and codebase health.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Demonstrated ongoing AI skill development, such as prompt/context engineering and agent orchestration, and staying current with emerging AI technologies.

Responsibilities

Manage multiple teams of ML engineers and technical leaders delivering large-scale systems infrastructure projects with significant organizational dependencies.
Shape and influence technical strategy and roadmaps for systems-level initiatives, translating long-term goals into executable plans.
Drive execution against engineering strategy by identifying and resolving blockers involving vision, technical direction, or team dynamics.
Evaluate architectural decisions, system design quality, and codebase health, using available tooling and direct contribution to maintain technical engagement across teams.
Build and grow the team by recruiting candidates, developing engineering leaders, and ensuring smooth onboarding.
Improve team workflows, tooling, and processes to raise the quality and reliability of systems.
Foster accountability, continuous improvement, and open communication, empowering engineers to raise concerns and take ownership.
Partner with product, design, data science, and infrastructure stakeholders to align systems investments with broader business and product goals.
Communicate technical context, risks, and progress to engineering leadership and cross-functional partners at all levels.
Hold engineering leaders accountable for performance management, upward feedback, and high standards of technical and operational excellence.