Cross-platform TV, streaming and digital ad measurement and optimization
VideoAmp builds measurement and optimization software that unifies audiences across linear TV, streaming and digital media. Its stack pairs a Rust/Tokio and Go systems layer with Iceberg, Parquet, DataFusion and an NVMe cache over S3, alongside Snowflake and Databricks, which points to an in-house query engine for large measurement datasets. Hiring is accelerating and sales-weighted, while job posts also describe agent infrastructure built on A2A APIs and MCP.
VideoAmp is a software and data company headquartered in Los Angeles, California, founded in 2014 and privately held, with 201–500 employees. Its platform gives advertisers and publishers measurement and optimization tools that connect audience data across traditional TV, streaming video and digital channels. Specialties include programmatic TV, cross-channel buying and measurement, and video advertising analytics. Customer-facing operations run on Salesforce, ChurnZero, Zendesk and Pendo, and current hiring is focused in the United States.
VideoAmp uses Rust, Go, C++ and Python with Tokio, Apache Iceberg, Parquet, DataFusion, Apache Spark, Snowflake and Databricks. It runs on AWS and GCP and uses Salesforce, Zendesk and Tableau.
Job posts describe several builds: an NVMe LRU cache over S3, a next-generation load balancing protocol, durable runtimes for long-running agent tasks, and multi-agent A2A APIs. The company is also scaling tune-in measurement for premiere events.
Yes. Sales leads VideoAmp's accelerating hiring mix, followed by engineering, ops and support. Most openings are senior or principal level, and all roles are in the United States.
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VideoAmp'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.