Design, build, and manage production-grade machine learning infrastructure on AWS, Azure, or GCP. Develop and optimize containerized AI applications using Docker and Kubernetes, and automate ML workflows with CI/CD and MLOps tools. Requires 3+ years of experience, strong Python skills, and business-level Japanese (JLPT N2 or above).
Key Highlights
On-site role in Tokyo, Japan
Design and manage cloud-based ML infrastructure
Build and optimize containerized AI applications with Docker and Kubernetes
Automate ML workflows and CI/CD pipelines
Business-level Japanese (JLPT N2) mandatory
Key Responsibilities
Design, build, and maintain cloud-based machine learning infrastructure using AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Develop and optimize containerized AI applications using Docker and Kubernetes (EKS, AKS, or GKE).
Build and manage Infrastructure as Code (IaC) using Terraform or CloudFormation.
Design and maintain CI/CD pipelines for machine learning applications using GitHub Actions or similar tools.
Develop and automate machine learning workflows using Airflow, Kubeflow, MLflow, Vertex AI Pipelines, SageMaker Pipelines, or equivalent platforms.
Deploy machine learning models into production using scalable serving frameworks such as KServe or SageMaker Endpoints.
Monitor infrastructure and model performance using Prometheus, Grafana, Datadog, and other observability tools.
Optimize cloud infrastructure performance, resource utilization, operational costs, and automate model retraining processes.
Looking to advance your Devops career with relocation support? Explore Devops Jobs with Relocation Packages that include comprehensive packages to help you move and settle in your new role.
Technical Skills Required
Python
Kubernetes
Cloud Computing
Benefits & Perks
Visa sponsorship
Relocation assistance
Discover our full range of relocation jobs with comprehensive support packages to help you relocate and settle in your new location.
Nice to Have
Familiarity with MLflow, Kubeflow, Airflow, Vertex AI, SageMaker, Prometheus, Grafana, or Datadog
Experience with Linux system administration
Cloud cost optimization experience
Professional English communication skills
Job Description
Our client is a global technology solutions provider specializing in Artificial Intelligence (AI), Cloud Computing, Data Engineering, and Digital Transformation (DX). The organization partners with enterprise clients across multiple industries to design, deploy, and operate scalable AI platforms that support machine learning, advanced analytics, and business automation.As enterprise adoption of AI continues to accelerate, the company is expanding its MLOps Engineering team to build production-grade machine learning infrastructure, automate AI deployment pipelines, and optimize cloud-native AI platforms using modern DevOps and MLOps technologies.
Want the full job description?
Read the complete details on LinkedIn, the original posting.
Continue on LinkedIn
This is a short excerpt. All rights to the full description belong to its original publisher.
