Senior Engineering Manager, Recommender Systems

Role overview Lead a backend engineering team responsible for the retrieval and ranking systems that power personalized recommendations. Shape the technical direction with machine learning and data science partners, balancing a responsive, high-quality user experience with system reliability and experimentation.

Responsibilities - Hire, coach, and retain a high-performing team focused on recommendation systems. - Own the reliability, latency, observability, and incident response of production recommendation services; identify quality or fairness regressions early. - Set technical strategy with strong attention to how recommendations affect the end-user experience. - Partner with machine learning colleagues on roadmaps, balancing product improvements with infrastructure and reliability work. - Work with data science to develop experimentation processes, tools, and practices.

Requirements - At least three years managing engineers, including hiring, performance management, career development, and delivery ownership. - Experience building or leading production recommender systems at scale. - Strong hands-on knowledge of high-throughput, low-latency distributed systems serving millions of users. - Expertise in Go, Java/JVM, or a comparable backend language, plus Postgres, a major cloud provider, and Kubernetes.

Nice to have - Experience with social networks or subscription marketplaces, including recommendation dynamics such as reciprocal interest, exposure, and marketplace liquidity. - Familiarity with machine learning and AI in modern recommendation systems. - Experience with retrieval technologies such as Elasticsearch/OpenSearch, vector search, or feature stores.

Benefits and work setup The role includes medical and dental coverage, equity, a daily food delivery allowance, unlimited vacation, and 12 weeks of paid parental leave. Employees also receive an annual travel stipend to visit somewhere new.