MLOps Engineer (f/m/div.)
Core
Define and evolve MLOps strategy for a hybrid cloud environment and implement scalable platforms covering the full ML lifecycle.
Role type
MLOps Engineer (Strategy & Architecture)
Builds
Scalable MLOps platform with self-service approach for data ingestion, feature engineering, model training, validation, deployment, and monitoring.
Domain
Automotive Electronics / Machine Learning Operations
Deliverable
production ML models
Required skills
Infrastructure as Code (IaC) with Terraform, Python scripting, Bash, Cloud solutions (Azure), Kubernetes, GitHub Actions, GNU/Linux systems, CI/CD pipelines, ML development process knowledge, DevOps principles.
Preferred skills
None stated.
Technologies
Terraform, Azure, Kubernetes, GitHub Actions, Python, Bash, GNU/Linux.
Responsibilities
Contribute to MLOps strategy definition and evolution; Design and implement IaC solutions; Ensure robust security practices; Develop and deploy new platform functionalities; Build and maintain monitoring dashboards and alerting systems; Collaborate with ML engineers, data scientists, and infrastructure teams.
Seniority
Mid-level, hands-on IC
