Senior Engineering Manager, Recommender Systems

Build, coach, and retain a high-performing backend team that specializes in recommender systems. 

Own reliable, low-latency production systems, observability, and incident response for recommendations. Catch regressions in latency, quality, or fairness before users notice.

Create and execute a technical strategy that is grounded in deep product intuition and empathy for the end-user experience. 

Partner with the Machine Learning team to define roadmaps. Balance user-facing improvements with investments in infrastructure, reliability, and experimentation.

Work with Data Science to co-own experimentation processes, tools, and best practices.

3+ years managing engineers, with direct responsibility for hiring, performance management, career development, and delivery.

Experience leading or building production recommender systems at scale. 

Hands-on depth in high-throughput, low-latency distributed systems that serve millions of users.

Expertise in Go, Java/JVM, or a similar backend language; Postgres, and AWS/GCP, and Kubernetes.

Experience with social networks or two-sided marketplaces in a subscription setting: you understand reciprocal interest, exposure, liquidity, and how great recommendations create long-term retentive value. 

Familiarity with how machine learning and AI fit into modern recommender systems.

Experience with retrieval infrastructure such as Elasticsearch/OpenSearch, vector search, or feature stores.