Overview
Hands-on engineering role focused on optimizing ML services and workflows.
Ideal candidate should have 3+ years in MLOps or related roles with strong cloud solution design skills.
hybridmidEnglishAWSGCPTerraformDockerKubernetesMLFlowGrafanaSQLNoSQL
Locations
Requirements
Strong understanding of cloud architectures Good understanding of modern MLOps best practices Experience with Infrastructure as Code tools Experience deploying ML models in production
Responsibilities
Build and manage automation pipelines Design and implement secure cloud architectures Contribute to MLOps best practices Bridge AI, Engineering, and DevSecOps Monitor production ML services