Senior Engineering Manager, Recommender Systems

Raya

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

Posted 11/5/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing high-performing backend teams specializing in recommender systems, with a strong focus on building reliable, low-latency production systems and collaborating with cross-functional teams to enhance user experience.

Highest-signal resume keywords

Team ManagementProduction Recommender SystemsHigh-Throughput Distributed SystemsGo ProgrammingAWS/GCP

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Team ManagementProduction Recommender SystemsHigh-Throughput Distributed SystemsGo ProgrammingJava/JVMPostgresKubernetesElasticsearchVector SearchFeature Stores

Soft Skills

CoachingEmpathyCollaboration

Tools & Technologies

AWSGCPKubernetesElasticsearchOpenSearch

Industry Keywords

Recommender SystemsMachine LearningAISubscription SettingSocial NetworksTwo-Sided Marketplaces

Tech Stack

Tools & technologies

AWSDistributed SystemsElasticSearchGoogle Cloud PlatformJavaKubernetesPostgresGo

About the role

Key responsibilities & impact

Build, coach, and retain a high-performing backend team specializing 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 grounded in 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

Requirements

What you’ll need

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, AWS/GCP, and Kubernetes
Experience with social networks or two-sided marketplaces in a subscription setting
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

Benefits

Comp & perks

Comprehensive medical and dental coverage
$50 a day food delivery budget
Equity based employment
Great culture
Learning opportunities
Unlimited vacation
12 weeks paid parental leave
$1,000 a year to travel somewhere in the world they’ve never been