- Technical leadership in MLOps/DevOps engineering area
- 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
- Develop monitoring solutions for our machine learning pipelines
- An excellent university degree (PhD is a plus) in natural science, mathematics, computer science, engineering or similar
- At least 5+ 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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Lead ML Ops Engineer - Munich, Deutschland - ZEISS Group
Beschreibung
Your Role
As Lead MLOps Engineer, you will be part of a growing team of machine learning experts. Your responsibilities will include:
Your Profile
Your ZEISS Recruiting Team:
Annett Burger, Huyen Trang Pham, Markus Repp