About this role
The engineer will architect and orchestrate a seamless multi-cloud environment, managing the AI tech stack and designing robust DataOps pipelines using the Medallion Architecture and Airflow. Key duties include implementing the MLOps lifecycle (CI/CD/CT/CM), championing cost efficiency for ML/LLM systems, and securing the platform via least-privilege access.
Candidates must possess 5+ years of technical experience with a proven track record of shipping ML pipelines in production, demonstrating deep expertise in multi-cloud environments (AWS, GCP) and Infrastructure as Code (Terraform). Essential qualifications include proficiency in DataOps, mastery of CI/CD automation via GitLab, expertise in containerization (Docker, Kubernetes), and a strong focus on cost management and efficiency.
What they're looking for
MLOpsMulti-CloudTerraformDataOpsMedallion ArchitectureAirflowCI/CDCT
Frequently asked questions
What does a Machine Learning Ops Engineer at Thunes do?
The engineer will architect and orchestrate a seamless multi-cloud environment, managing the AI tech stack and designing robust DataOps pipelines using the Medallion Architecture and Airflow. Key duties include implementing the MLOps lifecycle (CI/CD/CT/CM), championing cost efficiency for ML/LLM sy…
What skills does this Machine Learning Ops Engineer role need?
Key skills for this role include MLOps, Multi-Cloud, Terraform, DataOps, Medallion Architecture, Airflow.
How much does a Machine Learning Ops Engineer at Thunes pay?
The employer did not list a salary for this role. Most similar Singapore roles publish their band on the job page.
Is this Machine Learning Ops Engineer role remote, hybrid, or on-site?
This role is on-site, based in Singapore.
How do I apply for this Machine Learning Ops Engineer role?
You can apply directly on Thunes's careers page. ApplyLah can tailor your résumé and cover letter to this exact role in seconds first.