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Giotto.ai स्विट्ज़रलैंड की एक कृत्रिम बुद्धिमत्ता कंपनी है, जो उद्यमों के लिए संप्रभु रीजनिंग तकनीक विकसित करती है। इसका समाधान Giotto 1 को एक AI ऑपरेटिंग सिस्टम के साथ जोड़ता है। Giotto 1 एक उच्च-रीजनिंग मॉडल है, जिसे एक ही GPU पर चलाने के लिए बनाया गया है, जबकि AI ऑपरेटिंग सिस्टम में सहायक, दस्तावेज़ और कोड टूल, एकीकरण, एजेंट और निगरानी सुविधाएँ शामिल हैं। संगठन Giotto के यूरोपीय क्लाउड के माध्यम से इस प्लेटफ़ॉर्म का उपयोग कर सकते हैं, इसे निजी GPU पर तैनात कर सकते हैं या प्रमाणित Giotto-ready हार्डवेयर उपकरणों का इस्तेमाल कर सकते हैं। कंपनी का लक्ष्य विनियमित और तकनीकी टीमों को डेटा के भौगोलिक भंडारण, बुनियादी ढाँचे और निजी AI तैनाती पर अधिक नियंत्रण देना है।
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.
विवरण
- 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
आवश्यकताएँ
- 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
लाभ
- 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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