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Client:
ZEISS Group
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Job Category:
Other
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EU work permit required:
Yes
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Job Reference:
b3400de37366
Job Views:
2
Posted:
15.06.2025
Expiry Date:
30.07.2025
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Job Description:
Who we are:
We are a diverse and expanding team of Product Owners, Data Scientists, Machine Learning and MLOps Engineers.The team is built to support all ZEISS business units on their way to digitalization. We believe in the importance of cloud and software engineering in data science. Our focus is to build machine learning solutions in the Microsoft Azure cloud as well as ZEISS edge devices. As a team, we develop machine learning solutions based on structured and unstructured data, mainly using Python programming language. We rely on open-source code standards and aim to master our tools.
Your role
As an MLOps engineer, you will play a crucial role in shaping the future of Data Analytics and Machine Learning (ML) at ZEISS. You will be part of our Enterprise Data and Analytics team working together with machine learning experts. Your responsibilities will include:
Developing and monitoring solutions for our machine learning pipelines
Maintaining data and concept drift detection pipelines
Together with cloud engineers developing Azure cloud infrastructure using Terraform
Automate testing and documentation of machine learning code
Provide support and automation for ML templating ecosystem for our Data Scientists and ML Engineers
Take care of packaging, deployment, and distribution of our ML codebase
Your profile
An excellent university degree in computer science, natural science, mathematics, engineering, or similar
At least 3+ years of professional experience in MLOps, DevOps, or infrastructure engineering role
Proven experience in creating build and release pipelines for ML solutions
Proficiency in object-oriented programming with Python
Deep understanding of Python packaging and distribution ecosystem
Knowledge of infrastructure-as-code with Terraform (Azure cloud is a plus)
Hands-on experience in REST APIs and state-of-the-art cloud technologies (Azure cloud is a plus)
Expertise in virtualization technologies with Docker
Experience in container orchestration with Kubernetes (maintaining a K8s cluster is a plus)
Expertise in software engineering practices and version control with Git
Knowledge of data version control and ML metadata offerings are a plus (e.g. Azure ML, MLFlow, DVC)
Strong communication skills and collaborative team spirit
Fluent English (German language skills are a plus)
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