Giotto.ai
Giotto.ai
Giotto.ai — кәсіпорындарға арналған егеменді пайымдау технологиясын әзірлейтін швейцариялық жасанды интеллект компаниясы. Оның шешімі бір графикалық процессорда жұмыс істеуге арналған, пайымдау қабілеті жоғары Giotto 1 моделін ассистентті, құжаттармен және кодпен жұмыс істеу құралдарын, интеграцияларды, агенттерді және мониторингті біріктіретін жасанды интеллект операциялық жүйесімен ұштастырады. Ұйымдар платформаға Giotto-ның еуропалық бұлты арқылы қол жеткізе алады, оны жеке GPU-ларға орналастыра алады немесе Giotto-ға дайын сертификатталған аппараттық құрылғыларды пайдалана алады. Компания реттелетін салалардағы және техникалық командаларға деректердің орналасуы, инфрақұрылым және жеке жасанды интеллект орналастырулары үстінен көбірек бақылау беруге бағытталған.

Junior Machine Learning Engineer — Hybrid, Lausanne

Giotto.ai is hiring a junior machine learning engineer in Lausanne to develop and deploy Transformer-based AI systems. The role focuses on Python applications, data pipelines, and production-ready model services.

Сипаттама

  • Build and maintain Python components for machine learning applications
  • Integrate, fine-tune, and assess Transformer-based models
  • Contribute to data-processing, training, and inference pipelines
  • Assist with deploying models as dependable applications and services
  • Monitor and optimize model performance, latency, and resource consumption
  • Create tests and support code quality, documentation, and reproducibility
  • Troubleshoot issues spanning models, software, and infrastructure
  • Collaborate with researchers to convert experimental code into maintainable systems
  • Develop an understanding of deploying AI workloads across cloud, private, and on-premises infrastructure

Талаптар

  • Completed or nearly completed Master’s degree in computer science, artificial intelligence, machine learning, software engineering, or a related technical discipline
  • Advanced Python programming ability
  • Hands-on experience with PyTorch or another current machine learning framework
  • Working knowledge of large language models and Transformer architectures
  • Understanding of software engineering practices such as testing, version control, and maintainable code
  • Relevant experience from a thesis, internship, university project, open-source work, or personal project
  • Practical approach to problem-solving and willingness to work across the technology stack
  • Strong communication skills and a collaborative working style
  • Experience with Hugging Face, Docker, APIs, or Linux
  • Familiarity with vLLM, Ray, Kubernetes, or cloud GPU infrastructure
  • Experience deploying a machine learning model or application
  • Understanding of model inference, distributed computing, or performance optimization
  • Experience with CI/CD, experiment tracking, or data pipelines
  • Open-source contributions or other relevant technical projects

Артықшылықтар

  • Hybrid work arrangement
  • Regular collaboration from the Lausanne office
  • Hands-on exposure to model inference, data pipelines, APIs, GPU infrastructure, and production deployment
  • Collaboration with research and engineering teams
  • Practical opportunity to build, test, and deploy AI systems
  • Learning exposure to AI workloads across cloud, private, and on-premises infrastructure

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