Senior MLOps Engineer for ML Pipeline Automation

CloudWave Digital

Contract · Flexible hours

About the role

CloudWave Digital is building a scalable AI platform for real‑time analytics. We need a Senior MLOps Engineer to design, implement, and automate the end‑to‑end model deployment pipeline for a high‑throughput forecasting service.

Key responsibilities

• Architect and maintain CI/CD pipelines for ML models using GitOps principles.
• Containerize training and inference workloads with Docker and orchestrate them on Kubernetes.
• Integrate model monitoring, logging, and automated rollback mechanisms.
• Optimize resource usage and cost on AWS services such as SageMaker, EKS, and S3.
• Collaborate with data scientists to streamline model versioning and reproducibility.
• Ensure security and compliance across the deployment stack.

Must-have skills

• Extensive experience with Python for ML workflows.
• Deep knowledge of Docker and Kubernetes in production.
• Proficiency with AWS services (EKS, SageMaker, CloudWatch).
• Strong DevOps background, including CI/CD tools (GitLab, Jenkins, or similar).
• Hands‑on experience with model serving frameworks (TFServing, TorchServe, or similar).

Nice to have

• Familiarity with Terraform or CloudFormation for infrastructure as code.
• Experience with monitoring tools such as Prometheus and Grafana.