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Eviden, part of the Atos Group, with an annual revenue of circa € 5 billion is a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 53,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come .
Responsibilities: Development of Machine Learning and Deep Learning models for different use-cases. Investigate about the application of Federated Learning techniques to train Machine Learning models while preserving data privacy. Acceleration of models' training and inferencing using hardware accelerators. Integrate and tailor the resulting systems in different real-world use-cases. Assess the effectiveness of these systems and improve them over time. Adopt MLOps best practices and trustworthy AI standards to guarantee compliance with emerging regulations and good practices. Participation in European research projects. Education Requires a BS, Master, or PhD degree in Computer Engineering, Telecommunications Engineering, Electrical Engineering or other related disciplines. Essential knowledge and professional experience: 3+ years of experience in the areas of supervised and unsupervised machine learning.
3+ experience with data analytics and Machine Learning frameworks like Tensorflow, PyTorch, scikit-learn, Caffe2 or CNTK. Experience with scripting and programming languages such as Python or C/C++. Prepare software applications for their deployment using Docker and Kubernetes. Ability to work with software configuration management tools such as Git or GitLab. Knowledge of Continuous Integration/Delivery/Deployment. Advanced experience working with Linux. Additional knowledge Experience in using MLOps tools like Kubeflow or MLFlow. Experience with Federated Learning frameworks like Flower. Competences: Fluency in English. Good writing and presentation skills. Strong personal soft skills set communicative, enthusiastic, highly collaborative, proactive, and self-driven. Ability and enthusiasm to learn new technologies quickly. Half-day Fridays. Intensive workday in summer. Personalised training and upskilling programme. Flexible working hours and ways of working.
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