Descrizione dell'offerta
Junior Deep Learning Scientist (On-site)
2 days ago Be among the first 25 applicants
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.
Responsibilities
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.
- Work with data, compute and algorithms.
- Design deep learning multimodal neural architectures.
- Design experiments, implement them in code, run them on large (GPU on HPC) compute, run evaluations.
- Monitor and benchmark the state of the art.
- Give guidance to more junior team members such as PhD students and interns.
- Coordinate with our partners on our research roadmap.
- Adapt the project's pace to the rapid scientific development in our field.
- Organize publications and open-sourcing efforts.
Requirements
- Master's degree in AI, Computer Science, Deep Learning.
- Demonstrated research and work interests in foundation models.
- Excellent programming skills: Pytorch.
- Familiarity with Docker and Unix OS, including running GPU experiments.
- Interest in carrying out experimental research.
- Relevant scientific publications, teaching and research experience.
- Excellent command of English.
Bonus points if
- Strong in GPU training and inference optimization.
- Polyglot.
- Open-source contributions.
- Published at tier-1 ML/AI conferences such as NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV.
Headquarters
Translated is hosted at Pi Campus, a working environment immersed in nature where luxury villas in Rome (Italy) 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.
Benefits and Perks
At Translated, we see our people as athletes, and Pi Campus as the place where they can reach their full potential. This vibrant environment fosters talent aggregation and continuous growth of mind, body, and spirit. We nurture and support the team’s personal and professional development every day through growth-oriented initiatives like personalized learning paths and networking events with industry leaders, health-oriented initiatives like massages, sauna, and workouts in our gym and swimming pool, as well as relaxation rooms, open meeting rooms, a cafeteria, and fully equipped kitchens in every villa. In case of need, every team member has access to psychological, legal, and financial support. Learn more about our company:
Diversity Statement
At Translated, we proudly embrace and celebrate each individual’s unique qualities. 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.
Seniority level
- Entry level
Employment type
- Full-time
Job function
- Engineering and Information Technology
Industries
- Translation and Localization
Referrals increase your chances of interviewing at Translated by 2x
#J-18808-LjbffrApprofondimento sul ruolo
Translated, leader globale nel settore della traduzione tecnologica, ricerca un Junior Deep Learning Scientist da inserire nel suo team di Roma in modalità on-site. Un'opportunità stimolante per contribuire allo sviluppo di modelli di intelligenza artificiale avanzati in un ambiente science-driven che trasforma innovazione in impatto reale.
Il ruolo
Il candidato ideale avrà la responsabilità di contribuire al design e all'implementazione di Multimodal Foundation Models, lavorando con dati, algoritmi e risorse computazionali di alto livello. Sarà anche chiamato a coordinare attività tecniche, comunicative e di team, operando in un contesto dove la ricerca scientifica si trasforma rapidamente in soluzioni produttive. Un ruolo che unisce la ricerca teorica con l'applicazione pratica in ambito machine learning e AI.
Competenze valorizzate
- Deep learning e machine learning
- Modelli multimodali e fondazionali
- Programmazione Python e framework ML (TensorFlow, PyTorch)
- Gestione dati e algoritmi
- Comunicazione tecnica e team coordination
Lavorare a Roma
Roma rappresenta un hub crescente per l'innovazione tecnologica e l'AI in Italia, con una comunità in espansione di professionisti nel machine learning e nella ricerca scientifica. Translated consolida la sua presenza nella capitale italiana, offrendo opportunità di carriera in un'azienda con ambizioni globali e radici locali solide. La posizione on-site consente collaborazione diretta e integrazione immediata nel team di ricerca.
Domande frequenti
- Quali sono le responsabilità principali di un Junior Deep Learning Scientist (On-site)?
- Il ruolo prevede contribuzione al design e implementazione di modelli foundation multimodali, lavoro con dati e algoritmi avanzati, coordinamento di attività tecniche e team, operando in un contesto dove la ricerca scientifica si trasforma rapidamente in soluzioni di produzione.
- Quali requisiti sono fondamentali?
- Entusiasmo verso la progettazione di modelli AI avanzati, competenze solide in deep learning, capacità di coordinamento tecnico e comunicativo, esperienza con framework ML moderni e predisposizione a lavorare in un ambiente science-driven e innovativo.