DevOps Engineer

About the role

Later is seeking a DevOps Engineer to expand and maintain its cloud infrastructure, DevOps practices, and emerging MLOps capabilities. Reporting to the Infrastructure team, you will collaborate with senior engineers, platform teams, data scientists, and product engineers to build reliable systems for application delivery, data workflows, model experimentation, and machine‑learning deployment.

Key responsibilities

• Support the development and execution of the infrastructure roadmap across DevOps and MLOps, aligned with product and data‑AI growth plans.
• Partner with engineering, data, and ML teams to embed scalability, reliability, security, and automation into application and machine‑learning workflows.
• Evaluate, adopt, and integrate new DevOps and MLOps tools that improve efficiency, observability, developer experience, and operational reliability.
• Contribute to platform standards for infrastructure, CI/CD pipelines, data pipelines, and ML systems to make them repeatable and secure.
• Build and manage infrastructure for deploying ML models in production 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 a desire to deepen expertise in cloud infrastructure, Kubernetes, GitOps, and MLOps.
• Experience collaborating with engineering, data, and machine‑learning teams.
• Strong problem‑solving skills and a focus on reliability, security, and automation.

Required skills

• AWS (Amazon Web Services)
• Kubernetes
• CI/CD pipeline design and implementation
• Terraform
• Flask (for API development)
• Airflow
• Kubeflow
• Argo Workflows
• GitOps practices