Machine Learning Engineer (f/m/x)

At Corporate Research & Technology Department, we look at the innovations and developments of tomorrow. We research, analyse, advise and develop. All our ideas flow into future ZEISS products. We are looking for passionate and talented Machine Learning Engineer (f/m/x) to join our team and help drive the development of next-generation products and cutting-edge algorithms at ZEISS. Your RoleWe are seeking passionate and talented machine learning engineers who want to drive the development of next generation products and cutting-edge machine learning solutions at ZEISS.

Integrated in a team of scientists and research engineers at ZEISS Corporate Research & Technology you will develop algorithms and support end-to-end machine learning lifecycles taking ideas from academic and early stages to product launch. Working across the complete ZEISS product portfolio you will drive technology adoption and integration of latest advancements in machine learning, computer vision, imaging and optical metrology. Alongside the team, you will implement best practices to enhance the existing codebase and infrastructure with a focus on stability and scalability.

You will actively research, develop, and promote best practices, contributing to knowledge exchange within the team and the broader ZEISS machine learning community. During your work you will build an excellent network both within ZEISS and to external partners that help us to leverage the latest technology advancements to address tomorrow’s challenges. Your Profile An excellent university degree in computer science, engineering or similar – a Ph. D.

is a plusStrong proficiency in Python with professional software engineering experience (C++ and C# is a plus) Experience setting up CI/CD pipelines and container orchestration (Azure DevOps, Docker, Kubernetes is a plus)Skilled in Infrastructure as Code, cloud deployments, and automated infrastructure workflows (Azure, Ansible, Terraform is a plus)Familiarity with Machine Learning lifecycle tools (e. g.

MLflow, Kubeflow, DVC)Strong project management capabilities—including scope definition, milestone planning, risk mitigation, product backlog maintenance and cross-functional coordinationUnderstanding of Machine Learning (ML) algorithms and familiarity with modern Machine Learning librariesHands-on mindset coupled with strong communication and presentation skillsYour ZEISS Recruiting TeamFriederike Kirklar-Harms