Chalk builds data infrastructure that serves features and context to ML models and AI agents, deployed inside customer clouds on AWS and GCP. A Rust, C++ and Go core paired with Bazel, Starlark and Buildkite points to a performance-critical systems codebase, and hiring is accelerating and overwhelmingly engineering-led, with build speed, test flakiness and inference latency flagged as recurring internal pressures.
Chalk is a privately held company headquartered in San Francisco, California, with 51–200 employees. It sells a data platform that lets data science and ML teams build and run feature pipelines for use cases such as fraud prevention, healthcare, finance and product recommendations. The platform runs in the customer's own cloud environment, with infrastructure managed through Terraform across AWS and GCP. The company hires across the United States, Ireland, Israel, Japan, Singapore and Canada, and runs its go-to-market on Salesforce, HubSpot, Outreach and Marketo.
Chalk's engineering stack includes Rust, Python, Go, C++, TypeScript and React, built with Bazel and Buildkite, with Terraform managing AWS and GCP. Data tooling includes BigQuery, dbt, Looker and Tableau.
Yes. Hiring at Chalk is accelerating and heavily weighted toward engineering, mostly at mid and senior levels, with smaller openings in data, sales and product.
Chalk is hiring in the United States, Ireland, Israel, Japan, Singapore and Canada, with headquarters in San Francisco, California.
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Chalk'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.
