At ZEISS Corporate Research & Technology, we work at the frontier of science and technology. Our mission is to innovate and develop intelligent solutions contributing directly to future ZEISS products. We’re looking for a Machine Learning Engineer (f/m/x) who enjoys working across disciplines and is eager to develop intelligent systems that make a real difference for our consumers.
Your Role
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
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An excellent university degree in computer science, engineering or similar – a Ph.D. is a plus
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Strong proficiency in Python with professional software engineering experience (C++ and C# is a plus)
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Experience setting up CI/CD pipelines and container orchestration (Azure DevOps, Docker, Kubernetes is a plus)
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Skilled in Infrastructure as Code, cloud deployments, and automated infrastructure workflows (Azure, Ansible, Terraform is a plus)
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Familiarity with Machine Learning lifecycle tools (e.g. MLflow, Kubeflow, DVC)
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Strong project management capabilities—including scope definition, milestone planning, risk mitigation, product backlog maintenance and cross-functional coordination
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Understanding of Machine Learning (ML) algorithms and familiarity with modern Machine Learning libraries
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Hands-on mindset coupled with strong communication and presentation skills
Your ZEISS Recruiting Team:
Friederike Kirklar-Harms