About TranslatedTranslated 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 and frequently sponsor not only top-tier conferences, such as NeurIPS, ICML, ICLR, ACL and EMNLP but also open source implementations such as Meta's Voicebox. Our scientific innovations quickly make it to production and have a measurable impact on our operations. We're looking for a Deep Learning Scientist to join the Translated AI Research team in our HQ in Pi Campus, Rome. What You'll Do Together with another Deep Learning Scientist and a PhD student, you will be working on the DataTools4Heart (DT4H) project, collaborating closely with clinical partners and other research groups across Europe to develop innovative machine learning solutions for cardiovascular healthcare. Context At Translated, we are committed to leveraging cutting-edge machine learning to advance cardiovascular healthcare through our involvement in the DataTools4Heart project. This European Commission funded initiative aims to improve the diagnosis and treatment of cardiological diseases by developing a privacy-preserving cardiology data toolbox. The project brings together sixteen research groups and clinical organizations across Europe, focusing on multilingual natural language processing, federated learning, and differential privacy. Our work on DT4H: Our contributions to the DataTools4Heart project involve several challenging and impactful tasks, such as: Researching privacy-preserving methods for Large Language Models and generating realistic synthetic medical data to empower the development of medical AI models.Developing Machine Learning models to predict cardiovascular events by processing Electronic Health records (EHRs).Training and evaluating of (Large) Language and Machine Translation models specifically for the cardiovascular domain.We aim to publish our findings in top machine-learning conferences and journals, contributing to the advancement of medical natural language processing and privacy-preserving techniques in healthcare. In this role, you will be involved in the aforementioned tasks and: Conduct research to identify the right algorithms to solve these tasksImplement state-of-the-art Deep and Machine Learning algorithmsBuild robust training pipelinesDesign and run experimentsEvaluate and benchmark your resultsScrape and prepare the data for your models to learnStay up to date with the latest Deep Learning advancesPresent your results to other team members, management and fellow researchers from the consortiumPrepare and publish research findings in top machine-learning conferences and journalsQualifications RequiredRecent graduate from a master's or PhD program in relevant STEM discipline such as computer science, data science or mathematicsHands-on experience with Machine and Deep Learning projects including implementationExcellent programming skills in Python and familiarity with common Deep Learning libraries such as Pytorch, Huggingface and Scikit-LearnFamiliarity with Docker and Unix OS, including running GPU experimentsInterest in carrying out experimental researchProactive, goal-oriented self-starter with excellent time management skillsBonus points if you... have experience in medical AIare strong in multi-GPU training, GPU training optimizationare a polyglothave open-source contributionsHeadquartersTranslated is hosted at Pi Campus, a working environment immersed in nature where 5 luxury villas have been converted into functional offices to foster talent growth. Pi Campus is also a venture firm created by Translated to reinvest part of its profits into promising AI startups. Learn more about our company: https://translated.com/work-at-translated-onboarding Benefits and PerksOur working environment is both relaxed and intense. We are passionate about our mission, and our work is highly regarded in our industry. Competitive and exciting work environment. You will be surrounded by innovators and experts working at Pi Campus, a venture fund and startup ecosystem. A great environment to grow your skills.We host regular tech and entrepreneurship talks and events, in which you can take part as a Pi Citizen.GymSwimming PoolKickboxingFitnessPilates classesTable TennisFootball tableKitchen and snacksOther projects within the Translated AI teamMachine Translation: The team is pushing the boundaries of machine translation (MT) by exploring different routes to enhance translation accuracy such as context-awareness. Research focuses on refining translation quality in our production AI model, ModernMT, exploring methods to integrate inter-sentence dependencies and improve overall translation accuracy. With access to proprietary post-edited parallel datasets spanning Translated's twenty-year history, the team is driving innovation in language translation alongside our MT engineering and production team.Meetween: Translated spearheads the groundbreaking Meetween project, a 7M€, 4-year European research endeavor that leverages Large Language Models (LLMs) and multimodal foundation models to "solve speech". The project intersects research domains such as Deep Learning, Machine Translation, Automatic Speech Recognition and Translation, Summarization, and AI Digital Assistants. The team plays a pivotal role in advancing research outcomes, contributing to the development of foundation models capable of integrating text, audio, and video modalities within a unified architecture.Text to Speech: At Translated, we are at the forefront of Text-to-Speech (TTS) technology. Through projects like Matedub, we blend text translation with seamless voice synchronization. Our innovations include developing expressive synthetic voices, optimizing for reduced latency, and incorporating features like voice cloning and prosody control. Inspired by models such as VALL-E and Naturalspeech 3, we advance neural architecture and representation learning. Collaborating with our audio engineering team and using proprietary datasets, we create dynamic, lifelike synthetic voices. We further contribute with our work to the Voice For Purpose initiative by restoring voices for those who have lost them, showcasing our dedication to impactful technology.DiversityAt Translated, we proudly embrace and celebrate each individual's unique qualities to our team, regardless of race, sexual orientation, gender identity, or any other differences. We recognize that these diverse perspectives empower us to overcome challenges, foster innovation, and drive excellence. As an inclusive and equal-opportunity employer, we are committed to cultivating an environment where everyone feels welcome, valued, and supported to achieve their full potential. Privacy Policy
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