Philo operates a direct-to-consumer streaming platform with 70+ live TV channels and on-demand libraries. The tech stack reveals a data-first engineering culture: TensorFlow, PyTorch, Snowflake, dbt, and SageMaker sit alongside Roku, tvOS, and Android native codebases—typical of a company balancing ML-driven personalization (recommendation engine, content discovery) against real-time streaming and billing reliability. Active hiring is concentrated in data (3 roles) and engineering (3 roles) at senior/lead levels, with Apache Iceberg adoption underway, suggesting internal pressure to scale analytics and cost optimization across a maturing video platform.
Philo is a subscription video service headquartered in San Francisco, serving consumers who want live broadcast television without long-term contracts. The Essential plan includes 70+ channels (AMC, MTV, Hallmark, Discovery, etc.) plus 75,000+ on-demand titles, with a Bundle+ tier adding HBO Max, AMC+, and discovery+. The company operates a cross-platform streaming stack (iOS, Android, Roku, Fire TV, tvOS) and runs a data infrastructure spanning Snowflake, Redshift, Spark, and SageMaker. Core operational priorities center on billing analytics, subscription churn, content personalization, and video encoding—typical pain points for a mid-sized SVOD player managing licensing complexity and infrastructure costs.
Philo's production stack includes Python, AWS (EC2, SageMaker, Glue), Snowflake, dbt, TensorFlow, PyTorch, Segment, and Apache Spark for data/ML. Streaming clients run Roku, tvOS, iOS, Android (Kotlin, Jetpack Compose, ExoPlayer), and Amazon Fire TV.
Key projects include a next-generation video streaming pipeline, recommendation engine, content personalization, Apache Iceberg data storage migration, billing/subscription analytics dashboards, and per-query infrastructure cost optimization.
Philo'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.