Malt runs a freelance marketplace and freelance management system on a Kotlin/Spring Boot backend with GCP, Kubernetes, ArgoCD and a BigQuery/dbt/Looker data layer, while adopting Vue and Nuxt on the front end. Job posts cluster around payments: a payment architecture overhaul, cash advance and financing products, and a Head of Product Payment role. Sales hiring nearly matches engineering and targets outbound in Germany, pointing to an enterprise and SMB push beyond France.
Notable leadership hires: Product Payment Head
Malt, founded in 2013 and headquartered in Paris, operates a platform that connects organizations with independent professionals and supports sourcing, contracting, managing and paying freelancers. It positions itself as a freelance management system for companies, alongside its talent marketplace. The company employs 501–1,000 people and is privately held. Hiring is active in France, Germany and the United Kingdom across engineering, sales, support, design, finance and HR. Go-to-market runs on Salesforce, HubSpot, Marketo and LinkedIn Sales Navigator.
Malt uses Kotlin, Java and Spring Boot on the backend, TypeScript with Nuxt and Stencil on the front end, PostgreSQL, MongoDB, Elasticsearch and Redis, plus GCP, Kubernetes, Terraform, ArgoCD, BigQuery, dbt and Looker.
Yes. Hiring is accelerating, led by engineering and sales, with most openings at senior level. Roles are based in France, Germany and the United Kingdom.
Malt is overhauling its payment architecture, building payment, cash advance and financing products, decoupling its core systems, and launching outbound acquisition for German SMBs.
Other companies in the same industry, closest in size
Malt'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.