As Engineering Manager for Recommender Systems, you'll lead the team that builds the backend retrieval and ranking infrastructure behind recommendations at Raya. You'll partner closely with the head of ML to drive our tech strategy and ensure our members get the best experience possible on the core surface of our product.
We are looking for someone who is technically strong, has deep experience with production recommender systems, and has intuitive product-focused user empathy.
We offer comprehensive medical and dental coverage, $50 a day food delivery budget, equity based employment, a great culture, learning opportunities, unlimited vacation, 12 weeks paid parental leave, and we pay all employees $1,000 a year to go somewhere in the world that they’ve never been because of our values of human connection, empathy, and curiosity.
Responsibilities
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.
Qualifications
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.
What Sets You Apart
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.
Skills Required
- 3+ years managing engineers, including hiring, performance management, career development, and delivery
- Experience leading or building production recommender systems at scale
- Hands-on experience with high-throughput, low-latency distributed systems serving millions of users
- Expertise in Go, Java/JVM, or a similar backend language
- Experience with Postgres
- Experience with AWS or GCP
- Experience with Kubernetes
- Experience with social networks or two-sided subscription marketplaces
- Familiarity with machine learning and AI in modern recommender systems
- Experience with retrieval infrastructure such as Elasticsearch/OpenSearch, vector search, or feature stores
What We Do
Raya is a private community that fosters quality, real-world connection. We believe that value-driven communities create a strong sense of belonging, inspiring more learning, sharing, and compassion.
Why Work With Us
We’re a mission-driven team that cares deeply about working together to change the digital landscape. Everyone here is encouraged to learn and participate in professional development opportunities - and have some fun too. We regularly have team events, including karaoke, game nights, and hot pot dinners to get to know each other better.
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