Senior Deep Learning Scientist
Pubblicato il 15-10-2026 - Translated in Roma
About Translated Translated is on a mission to allow everyone to understand and be understood, in their own language. We are a technology-powered professional translation provider. We partner with over 200 000 professional translators worldwide, in 200 languages. Our 310 000 clients range from the private person who needs their CV translated to the very big, like Uber and Airbnb.
About Translated Translated is on a mission to allow everyone to understand and be understood, in their own language. We are a technology-powered professional translation provider. We partner with over 200 000 professional translators worldwide, in 200 languages. Our 310 000 clients range from the private person who needs their CV translated to the very big, like Uber and Airbnb. Our progress is largely powered by our ability to leverage scientific progress and realize the best synergy between humans and machines. We invest heavily in R&D;, such as LLMs applied to translation, expressive speech synthesis, and privacy-preserving training for translation. We operate as a science-driven startup,
so that our scientific innovations quickly make it to production and make a measurable impact on our operations. The ideal candidate should have a strong enthusiasm for contributing to the design and implementation of Multimodal Foundation Models. Additionally, they should be capable of coordinating technical, communication, and team activities. The project: DVPS. Translated has been awarded funding for the DVPS project, a collaborative research initiative worth 29 million euros over 4 years, which will be led by Translated. DVPS develops the science of multimodal foundation models and applies them to problems in the fields of Earth observation, language, and cardiology. DVPS is an acronym for the project’s motto, “Diversibus Viis Plurima Solvo”, meaning “Through various paths, I solve many problems.” The project has computing resources that match its ambition. It is estimated to use 30 million GPU-hour