We 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 prototypes. 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.

a university degree in computer science, engineering or similar – a Ph.D. is a plus

professional experience in software engineering, DevOps or machine learning related roles

deep understanding of machine learning & deep learning algorithms and strong interest in algorithmic stability monitoring

strong record of programming in Python or C++ with solid knowledge of modern ML techstacks

proven experience in CI/CD solutions, virtualization technologies and container orchestration – state of the art cloud providers is a plus

hands-on mindset coupled with strong communication and presentation skills

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