Senior MLOps Engineer – Feature Engineering

CoreData Systems

Contract · Flexible hours

About the role

CoreData Systems is seeking a senior MLOps Engineer to lead the end‑to‑end deployment of a high‑impact machine learning solution. You will collaborate with data scientists and software engineers to transform prototypes into production‑ready services.

Key responsibilities

• Design and implement CI/CD pipelines for model training, validation, and serving.
• Containerize ML workloads using Docker and orchestrate them on Kubernetes.
• Automate infrastructure provisioning and scaling on AWS.
• Monitor model performance, drift, and resource utilization in real time.
• Establish logging, alerting, and rollback procedures for robust operations.
• Document best practices and handover procedures for the engineering team.

Must-have skills

• Extensive experience with Python for scripting and automation.
• Deep knowledge of Docker and Kubernetes in production environments.
• Proficiency in AWS services such as SageMaker, EKS, and CloudWatch.
• Strong background in DevOps principles and CI/CD tooling.
• Ability to troubleshoot complex distributed systems.

Nice to have

• Familiarity with Terraform or CloudFormation for IaC.
• Experience with model monitoring frameworks like Prometheus or Grafana.