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Giotto.ai
Giotto.ai
51 – 200 Employees
Artificial IntelligenceEnterpriseHardware
Giotto.ai is a Swiss artificial intelligence company building sovereign reasoning technology for enterprise use. Its offering combines Giotto 1, a high-reasoning model designed to run on a single GPU, with an AI operating system that brings together an assistant, document and code tools, integrations, agents, and monitoring. Organizations can access the platform through Giotto’s European cloud, deploy it on private GPUs, or use certified Giotto-ready hardware appliances. The company focuses on giving regulated and technical teams greater control over data residency, infrastructure, and private AI deployments.
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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.

CHSwitzerlandHybridFull-timeJuniorEnglish RequiredMachine Learning Engineer
CloudDockerKubernetesLinuxPythonPyTorchRay

Description

  • 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

Requirements

  • 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

Benefits

  • 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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