Giotto.ai
Giotto.ai
Giotto.ai este o companie elvețiană de inteligență artificială care dezvoltă tehnologie suverană de raționament pentru utilizare în organizații. Oferta sa combină Giotto 1, un model cu capacități avansate de raționament conceput să ruleze pe un singur GPU, cu un sistem de operare pentru inteligență artificială care reunește un asistent, instrumente pentru documente și cod, integrări, agenți și monitorizare. Organizațiile pot accesa platforma prin cloudul european Giotto, o pot implementa pe GPU-uri private sau pot utiliza echipamente hardware certificate și pregătite pentru Giotto. Compania se concentrează pe oferirea unui control mai mare echipelor din domenii reglementate și echipelor tehnice asupra rezidenței datelor, infrastructurii și implementărilor private de inteligență artificială.

Junior AI Researcher at Giotto.ai — Hybrid, Lausanne

Join Giotto.ai as a Junior AI Researcher in a hybrid Lausanne role. Train and evaluate advanced models, develop benchmarks, and help turn research ideas into production-ready AI systems.

Descriere

  • Review current AI research and turn relevant ideas into practical experiments
  • Train, fine-tune, and assess Transformer-based models
  • Support research on reasoning, synthetic data, model adaptation, and evaluation
  • Create benchmarks and investigate model performance and failure patterns
  • Test ways to improve training data, objectives, prompts, and inference strategies
  • Develop clear, reproducible research software
  • Record experiments, findings, and conclusions
  • Work with research, engineering, and product teams
  • Build understanding of how advanced research becomes production-ready AI systems

Cerințe

  • Completed or nearly completed a master’s degree in computer science, artificial intelligence, machine learning, mathematics, physics, or another quantitative discipline
  • Strong foundation in machine learning and deep learning
  • Hands-on Python and PyTorch experience from academic projects, a thesis, research, or an internship
  • Working knowledge of Transformer architectures and large language models
  • Understanding of probability, statistics, linear algebra, and optimization
  • Ability to interpret research papers and implement their proposed methods
  • Intellectual curiosity, analytical ability, and motivation to learn
  • Effective communication and a collaborative approach
  • Experience with Hugging Face Transformers or Datasets
  • A master’s thesis focused on LLMs, reasoning, multimodal learning, reinforcement learning, interpretability, or generative AI
  • Experience with model fine-tuning, LoRA/PEFT, synthetic data, or evaluation workflows
  • Research publications, open-source work, or relevant personal projects
  • Familiarity with GPUs, experiment-tracking platforms, or cloud infrastructure

Beneficii

  • Hybrid work arrangement
  • Regular team collaboration at the Lausanne office

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