Machine Learning Engineer

SIXT is a global market leader in the mobility space and sets the pace for innovation like nobody else. We are transforming the industry to become fully digitalized and offer our customers an answer to all mobility needs they have. Our vision is: Transform the world moves, because people expect better. Join our Data Science team and make the magic happen. We drive business processes like pricing and many more with the use of sophisticated algorithms. For this purpose, we design, develop and maintain state of the art machine learning models and manifold optimization solvers as well as simulation models. As a member of this team, your work will improve the experience of millions of our customers and have a direct impact on our business results. Apply now and join our journey and become a part of the SIXT family.

DO WHAT YOU LOVE:

• Develop further and maintain a solid infrastructure within the Data Science team, with a focus on DevOps processes and cloud technologies.
• Establish and extend tools to automate our Data Science Tech Stack to continuously enhance MLOps processes, including model deployment and data pipelines.
• Ensure a reliable and scalable deployment foundation for our Data Science ML models and algorithms and work closely with other departments like cloud infrastructure.
• Collaborate effectively with stakeholders from other departments to achieve our business goals.
• Build and maintain infrastructure as code (IaC) using tools like Terraform to manage cloud resources.
• Make data science experiments production-ready, monitored, robust, and scalable

Requirements

COME AS YOU ARE:

• Strong knowledge cloud technologies, ideally in AWS
• Solid coding skills in Python and experience with continuous integration/continuous deployment approaches.
• Experience with infrastructure as code (IaC), ideally Terraform, is a strong plus
• Familiarity with containerization technologies such as Docker and ideally container orchestration systems such as Kubernetes.
• Ideally knowledge in operational deployment of machine learning applications
• Ideally knowledge of data engineering, including data modeling, database systems, and ETL processes.
• Ideally experience with monitoring and logging tools to detect and diagnose issues in machine learning models and the infrastructure supporting them.
• Excellent communication and collaboration skills, with fluency in English and an appreciation for cultural diversity.