Private social network connecting people for relationships, friendship, and collaboration
Raya operates a membership-based social platform focused on facilitating real-world connections across relationships, friendship, and professional collaboration. The tech stack reveals a dual-layer architecture: modern identity and device management (Okta, Kandji, Fleet) paired with ML-heavy backend infrastructure (PyTorch, TensorFlow, Kafka, Spark, Elasticsearch). Active projects center on recommendation systems, embedding-based retrieval, and ranking pipelines—indicating the core product challenge is surfacing high-signal matches at scale. Hiring velocity is accelerating with senior-level roles concentrated in engineering and data, suggesting investment in ML infrastructure to handle growth in matching quality.
Founded in 2015, Raya is a private membership community designed for global citizens seeking life partners, friendships, and professional collaborations. The platform operates with strict curation and privacy controls, enabled by a tech stack spanning device lifecycle management (Kandji, Fleet), identity (Okta), and backend services in Python, Go, and Node.js. The company maintains engineering and support presence across Los Angeles, New York, London, Paris, Berlin, Barcelona, and Mexico City. Current focus areas include scaling recommendation systems, improving device reliability, and maintaining security baselines—operational concerns typical of a consumer network managing high trust requirements.
Backend: Python, Go, Node.js, PostgreSQL, MongoDB, Elasticsearch. Data pipeline: Kafka, Apache Spark, dbt. ML: PyTorch, TensorFlow, Transformers. DevOps: Kubernetes. Identity: Okta, 1Password. Device management: Kandji, Fleet.
Raya hires in the United States and Peru. Office locations span Los Angeles, New York, London, Paris, Berlin, Barcelona, and Mexico City.
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Raya's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.