Senior Engineering Manager, Recommender Systems (Remote)

This is a people-leadership and technical role at a consumer app company with a subscription model and a strong social component. You will lead the backend team that powers how content and member recommendations are retrieved and ranked on the product's core surface. The role works closely with the head of machine learning to set technical direction and balance user-facing features against reliability and experimentation work.

What you'll do

• Hire, coach, and grow a backend engineering team focused on recommender systems, and manage performance and career development.
• Own the reliability, latency, and observability of production recommendation services, including incident response.
• Detect regressions in latency, recommendation quality, or fairness before they reach users.
• Set a technical strategy grounded in product understanding and empathy for the end-user experience.
• Co-plan roadmaps with the machine learning team, weighing user-facing work against infrastructure and experimentation investment.
• Share ownership of experimentation processes, tooling, and best practices with the data science team.

What you need

• 3+ years managing engineers, including direct responsibility for hiring, performance reviews, and delivery.
• Experience leading or building production recommender systems at scale.
• Hands-on depth with high-throughput, low-latency distributed systems serving millions of users.
• Strong backend skills in Go, Java/JVM, or a similar language, plus Postgres, AWS or GCP, and Kubernetes.
• Nice to have: experience with social networks or subscription-based two-sided marketplaces, familiarity with modern ML and AI in recommendations, and experience with retrieval infrastructure such as Elasticsearch/OpenSearch, vector search, or feature stores.

How to apply

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