Das ist der Job
In this role
• As a Senior AI Engineer, you will take the technical lead in exciting data science and AI/ML projects.
Darum lohnt es sich
You will be responsible for the design, development and implementation of solutions in these areas.
• Realize end-to-end data science and AI/ML projects from requirement to delivery
• Analysis and modelling of data as well as evaluation and communication of the results to various stakeholders
• Model complex business problems with machine learning: You will select appropriate methods and models, adapt them to customer data and optimize them if necessary
• Create processes and data pipelines to prepare raw data for model training and inference
• Create, maintain, and optimize MLOps pipelines to automate model training, deployment, and monitoring
• Close cooperation with interdisciplinary IT and engineering teams
• Imparting technical know-how and supervising junior data scientists.
Git, JIRA, Microsoft Teams)
• Knowledge of cloud technologies (Azure, AWS, Google Cloud) and big data platforms (e.g.
Spark, Databricks) is an advantage
• Strong analytical and problem-solving skills.
• Flexibility to travel around Romandie
• Good communication skills, ability to create and sustain client relationships
• Fluent in French and English
What we offer
• A stimulating and professional working environment in a dynamic team with extensive expertise
• Exciting projects and challenging problems to solve using the latest technologies
• Flat organizational hierarchies and cross-functional teamwork
• Close contact with customers in diverse industries
• A supportive culture with excellent opportunities for professional and personal development What you bring
• A degree from a technical university
• At least 5 years of experience in the AI field as a data scientist, ML engineer or similar position
• Sound knowledge of Python or other programming languages.
Experience with data science and machine learning frameworks (e.g. scikit-learn, TensorFlow, PyTorch), data analysis tools (e.g. pandas) and MLOps tools (e.g. MLflow)
• Sound knowledge of Windows, Linux, network technology, data storage, web services as well as software engineering and collaboration tools (e.g.
