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описание
The company builds interactive, resettable digital environments where AI agents navigate software, complete tasks, fail, and improve. Data is a fundamental input to the development of AI systems and training environments.
задачи
Design and build scalable systems for acquiring, ingesting, and integrating large, messy, and varied datasets;
Develop robust validation, sanitisation, and PII-removal layers to ensure data safety and quality;
Tackle complex data problems, including duplication, corruption, inconsistent formats, and provenance;
Make critical architectural decisions across storage, reliability, observability, security, and cost;
Ensure reliable, high-quality data availability for AI training environment engineers.
требования
Built and operated substantial production data systems end-to-end, owning architecture, implementation, and production behaviour;
Strong software engineering fundamentals and deep hands-on coding experience beyond configuring tools;
Experience with large, complex, or messy datasets, including unstructured text, web, and machine-generated data;
Ability to articulate challenges associated with complex datasets;
Sound judgement across storage, processing, reliability, scalability, and cost, with the ability to discuss trade-offs;
Comfortable with cloud infrastructure and debugging complex production systems.
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