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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries

Main duties and responsibilities

• We are looking for AI Research Software Engineers with expertise in one or more of the following areas:, , • Distributed AI training and optimization, • Data curation (text and multimodal), • Model evaluation and benchmarking, • Inference systems and deployment, • Reasoning , • Multi-modal AI models
• MSc in Computer Science, Data Science, AI or related field (exceptional BSc candidates will also be considered)
• Experience in AI and neural network architectures
• Strong programming skills in Python and knowledge of PyTorch or similar ML frameworks
• Experience with software development practices, including version control systems, debugging, testing, and deployment
• Excellent problem-solving abilities and strong analytical skills
• Ability to work effectively in a team as well as independently

We offer

• A stimulating academic environment at one of the world's leading technical universities
• The opportunity to work with state-of-the-art supercomputing infrastructure and cutting-edge AI research
• Collaboration with top researchers and engineers from EPFL, ETH Zurich, CSCS, and other Swiss institutions
• Flexible working arrangements, including options for remote work
• Professional development opportunities, including conference attendance and specialized training
• The chance to contribute to open-source projects with global impact
• Access to the broader Swiss academic ecosystem and industry partnerships
• Being part of Switzerland's sovereign AI development, working on technology with national significance

Duration: 1 year, renewable