AI platform automating translation and localization for global enterprises
Smartcat runs an AI-driven content localization platform on a polyglot stack spanning .NET Core, Python, Java and Vue across AWS, Azure, GCP and OCI. The ML layer (PyTorch, Transformers, Weights & Biases, Label Studio, OpenAI GPT API) points to in-house model tuning, while Databricks, dbt, Airflow and Kafka plus a legacy batch-to-streaming migration show data infrastructure being rebuilt. Hiring is accelerating and sales-led, focused on enterprise expansion and new logos.
Notable leadership hires: Sales Director
Smartcat, founded in 2016 and headquartered in Wilmington, Delaware, builds an enterprise AI platform for creating, translating and localizing content across documents, websites and software. AI agents handle much of the workflow, with a marketplace of vetted human linguists and editors available for content needing human review. The company sells to global enterprises and reports more than 1,000 companies as customers. It is privately held, employs 201–500 people, and hires across Portugal, Serbia, the United States, the United Kingdom and Armenia.
Smartcat uses .NET Core, Python, Java and Vue, with MongoDB, PostgreSQL, Elasticsearch and Kafka, running on Kubernetes across AWS, Azure, GCP and OCI. Data and ML tools include Databricks, dbt, Airflow, PyTorch and the OpenAI GPT API.
Yes. Sales is Smartcat's dominant hiring area, skewed toward senior and director-level roles including a Sales Director, focused on enterprise new-logo acquisition, account expansion and ABM outbound campaigns.
Smartcat is hiring in Portugal, Serbia, the United States, the United Kingdom and Armenia, with headquarters in Wilmington, Delaware.
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Smartcat'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.