DevOps Engineer (Cloud & MLOps)

About the role

Later, the AI‑powered influencer marketing platform, is looking for a DevOps Engineer to support and grow its cloud infrastructure, DevOps practices, and emerging MLOps capabilities. The role will work closely with senior engineers, platform teams, data scientists and product engineers to build reliable systems for application delivery, data workflows and machine‑learning deployment.

Key responsibilities

• Support the development and execution of the infrastructure roadmap across DevOps and MLOps, aligned with product and data growth plans.
• Partner with engineering, data and ML teams to embed scalability, reliability, security and automation into application and ML workflows.
• Evaluate, adopt and integrate new DevOps and MLOps tools that improve efficiency, observability and developer experience.
• Contribute to platform standards that make infrastructure, CI/CD pipelines, data pipelines and ML systems repeatable and secure.
• Build and manage cloud‑native infrastructure to deploy ML models using CI/CD pipelines, Flask‑based APIs and orchestration tools such as Airflow, Kubeflow or Argo Workflows.
• Automate training pipelines, model registries and related repeatable tasks.

Required profile

• Solid foundation in DevOps with hands‑on experience in cloud infrastructure.
• Interest in deepening expertise in Kubernetes, GitOps and MLOps.
• Ability to collaborate with senior engineers, data scientists and product teams.
• Strong problem‑solving mindset and focus on reliability and automation.

Required skills

• AWS
• Kubernetes
• Terraform
• CI/CD pipelines
• GitOps
• MLOps
• Airflow
• Kubeflow
• Argo Workflows
• Flask