Design, deploy, and operate scalable cloud infrastructure for enterprise machine-learning and AI applications in Tokyo. Manage container orchestration, CI/CD pipelines, and ML model deployment across AWS, Azure, or Google Cloud. Requires business-level Japanese (JLPT N2+), professional English, and 3+ years of experience in MLOps or cloud engineering.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
MLOps Engineer – Cloud AI Platform
Location: Tokyo, Japan
Employment type: Permanent
Working arrangement: Office-based
Salary: ¥7,000,000–¥15,000,000 per year
Visa sponsorship: Available
Relocation support: Available
Important language requirement:
Business-level Japanese equivalent to JLPT N2 or higher is mandatory.
Applicants must be able to complete technical interviews and communicate with clients and internal stakeholders in Japanese. Professional English is also required for collaboration with international engineering teams.
The opportunity
Global Engineering Talent is supporting a major international technology and digital-transformation organisation with the continued expansion of its machine-learning and AI infrastructure capability in Tokyo.
We are looking for an experienced MLOps Engineer to design, deploy and operate scalable cloud infrastructure supporting enterprise machine-learning and AI applications.
This is a hands-on engineering position covering cloud platforms, container orchestration, infrastructure as code, CI/CD, ML pipelines, model deployment, monitoring and production reliability.
You will collaborate with AI engineers, data scientists, software developers and international delivery teams to move machine-learning solutions from development into secure, reliable and cost-effective production environments.
Responsibilities
- Design, build and operate machine-learning infrastructure across AWS, Azure or Google Cloud
- Containerise AI and machine-learning applications using Docker
- Deploy and operate workloads using Kubernetes, including EKS, AKS or GKE
- Provision and manage cloud infrastructure through Terraform or CloudFormation
- Design and maintain CI/CD pipelines for machine-learning services
- Build automated data, training and inference pipelines
- Deploy models into scalable production environments
- Implement model versioning, experiment tracking and registry processes
- Monitor model performance, latency, infrastructure health and resource utilisation
- Establish alerting, logging and incident-response processes
- Automate model retraining and production-release workflows
- Improve the reliability, security and reproducibility of ML systems
- Estimate, monitor and optimise cloud and GPU infrastructure costs
- Work with Japanese clients and internal stakeholders to understand technical requirements
- Collaborate with global and offshore engineering teams
- Research and evaluate emerging MLOps, cloud and AI-platform technologies
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Essential requirements
- Business-level Japanese equivalent to JLPT N2 or higher
- Ability to complete a technical interview and discuss architecture in Japanese
- Strong professional experience in at least one of the following areas:
- Python software development
- Cloud infrastructure or cloud operations
- Docker and Kubernetes
- Infrastructure as code
- CI/CD engineering
- Linux systems
- Machine-learning or data platforms
- Commercial experience with AWS, Azure or Google Cloud
- Understanding of the machine-learning lifecycle from development through deployment and operation
- Ability to work effectively with AI engineers, data scientists and software-development teams
- Strong troubleshooting and technical communication skills
- Approximately three or more years of relevant engineering experience
Highly desirable experience
- Kubernetes, EKS, AKS or GKE
- Terraform or CloudFormation
- GitHub Actions, GitLab CI/CD, Jenkins or Azure DevOps
- AWS SageMaker, Google Vertex AI or Azure Machine Learning
- Airflow, Kubeflow or other workflow-orchestration platforms
- MLflow or another model registry and experiment-tracking platform
- KServe, SageMaker Endpoints or other production model-serving technologies
- Prometheus, Grafana, Datadog or comparable monitoring tools
- Automated model retraining and deployment
- GPU infrastructure and inference optimisation
- Cloud cost estimation and optimisation
- Spark, Hadoop or large-scale data processing
- Microservices and API-based architecture
- Production incident management and operational support
- Previous experience working in Japan
- Experience collaborating with overseas or offshore engineering teams
- Applying AI tools to improve engineering efficiency and quality
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Why consider this opportunity?
- Work on enterprise-scale AI and machine-learning infrastructure
- Take ownership of systems supporting production AI applications
- Collaborate with specialists across an international technology organisation
- Gain exposure to modern cloud, Kubernetes and MLOps platforms
- Contribute to the continued expansion of an established AI capability in Japan
- Salary up to ¥15 million depending on experience
- Visa sponsorship and relocation assistance available
- Streamlined interview process
How to apply
Please apply with your CV and include:
- Your Japanese level and JLPT qualification
- Whether you can complete a technical interview entirely in Japanese
- Your current location and visa status
- Your current and expected salary
- Your notice period or earliest available start date
- A brief example of a production ML platform or model-deployment environment you have personally built or operated
- The cloud, Kubernetes, infrastructure-as-code and CI/CD technologies you have used commercially
Applications without business-level Japanese equivalent to JLPT N2 or higher cannot be considered.
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