MLOps Engineer

You will design, build, and maintain machine learning infrastructure as an experienced Kubernetes developer.

Responsibilities

• Design and develop scalable ML pipelines using LakeFS for data versioning and Kubeflow for workflow orchestration.
• Build, scale, and manage Kubernetes and Docker containers to support machine learning workloads.
• Deploy and monitor Kubernetes clusters to ensure efficient execution of ML tasks.
• Implement and optimize CI/CD pipelines for rapid model updates and deployment.
• Collaborate with data scientists and software engineers to integrate models into production and troubleshoot performance.

Required Skills

• 6+ years of professional experience in technical roles.
• Deep expertise in Kubernetes and Docker containerization.
• Hands-on experience with Kubeflow and LakeFS.
• Proficiency in Python.
• Strong understanding of CI/CD processes and ML pipeline architecture.
• Knowledge of data versioning and the current AI landscape.
• Degree in any graduate field.