Machine Learning Engineer (m/f/x)
Core
Architecting and maintaining MLOps infrastructure to bridge experimental research with production-grade software for ZEISS products.
Role type
Senior Machine Learning Engineer (MLOps & Platform)
Builds
Robust MLOps infrastructure, production-ready Python/C++ software packages, automated CI/CD pipelines, and scalable research computing environments.
Domain
Optics & Photonics / Enterprise Software Engineering
Deliverable
production ML models | infrastructure
Required skills
Python, C++ or C#, Docker, Kubernetes, Terraform, Ansible, Azure DevOps, GitHub Actions, MLflow, Kubeflow, DVC, Git, CI/CD pipeline design, Infrastructure as Code (IaC), system monitoring and logging
Preferred skills
C#, high-performance hardware integration, mentoring researchers, technical scope definition
Technologies
Python, C++, C#, Docker, Kubernetes, Terraform, Ansible, Bicep, Azure, Azure DevOps, GitHub Actions, MLflow, Kubeflow, DVC, ELK stack, Git
Responsibilities
Design and maintain MLOps infrastructure for seamless transition from experimentation to production; Transform experimental research code into modular, high-performance software packages; Build and manage automated testing, building, and deployment pipelines; Provision and scale research computing environments using IaC; Define and promote engineering standards for version control, containerization, and code quality; Implement monitoring and logging solutions for model performance and system health; Consult with scientists to optimize workflows and navigate cloud/hardware environments.
Seniority
Senior, hands-on IC with project leadership