Machine Learning Operation Engineer (f / m / x)

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)

Your ZEISS Recruiting Team :

Huyen Trang Pham, Markus Repp