Software Engineering Manager, Recommendation Systems

Meta is looking for a Software Engineering Manager to lead a team building and advancing recommendation systems that power personalized experiences for billions of people across Meta's family of apps. In this role, you will drive the technical strategy and execution of ranking, retrieval, and recommendation infrastructure, partnering closely with product, data science, and infrastructure teams to deliver high-impact improvements to relevance, engagement, and user satisfaction at massive scale.

Lead a team of engineers building and optimizing recommendation and ranking systems across retrieval, scoring, and re-ranking stages Drive roadmap creation for recommendation infrastructure, balancing near-term delivery with long-term technical investments Contribute hands-on to technical decisions, including system architecture, model serving pipelines, and feature engineering frameworks Partner with data science, product, and infrastructure teams to align recommendation system development with business and product goals Identify and resolve bottlenecks in recommendation quality, latency, and engineering efficiency, including oncall load and technical debt Set clear goals and expectations for team members, provide timely and actionable feedback, and actively develop engineers' technical capabilities Manage staged rollouts and experimentation frameworks to evaluate recommendation changes and measure impact on key engagement metrics Communicate team strategy, technical decisions, and progress clearly to engineering peers, product partners, and leadership Proactively identify opportunities for automation and tooling improvements that expand the team's scope and efficiency Participate in recruiting, onboarding, and org-level contributions to strengthen the broader recommendation systems engineering community

4+ years of experience in software engineering working on recommendation systems, ranking, or related machine learning infrastructure 2+ years of experience managing software engineering teams, including setting goals, providing feedback, and driving team execution Experience contributing hands-on to technical decisions in recommendation or ranking systems, including architecture, feature pipelines, or model serving Experience driving cross-functional collaboration with product, data science, and infrastructure partners to deliver measurable outcomes Experience identifying and resolving engineering efficiency issues such as technical debt, oncall burden, or system scalability constraints Familiarity with distributed training, model serving infrastructure, or real-time feature computation in the context of recommendation systems Experience using experimentation frameworks to measure and iterate on recommendation quality and engagement metrics Experience leading teams that have shipped large-scale recommendation or personalization systems from inception to production impact Track record of growing engineers' technical skills and expanding team scope through effective delegation and mentorship