Job Description:

Business Overview

Our Rakuten Group mission is to empower people and society through innovation. The Group offers more than 70 diverse services, including e-commerce services such as - Internet shopping mall, financial services such as , Mobile network operator business - , and professional sports.

Department Overview

AI Engineering Supervisory Department, under the Tech Division, leads the transformation of Rakuten by commercialization of Artificial Intelligence, Cognitive Computing and Machine Intelligence Technologies for Rakuten businesses.

With access to Rakuten’s ecosystem of more than 70 services, global businesses and technology expertise across Asia, Europe and the Americas, IDX – Insights and developer experience is to create tools and technologies to support experimentation, insight creation, tool creation, and ML Serving. Some examples of what we are working on is embedding deep learning models over GPU serving at scale for various important AI initiatives. Tools team works on creating data validation / model validation tools, model evaluation tools etc.

Position:

Position Details

- Kubernetes Infrastructure: Design, build, and manage Kubernetes clusters, ensuring high availability, scalability, and security.

- CI/CD Pipelines: Implement and enhance CI/CD pipelines for automated deployment and continuous integration.

- Containerization: Expertise in Docker and container orchestration using Kubernetes.

- Microservices Architecture: Collaborate with development teams to optimize microservices-based applications.

- Troubleshooting: Diagnose and resolve issues related to Kubernetes, pods, services, and networking.

- Infrastructure as Code (IaC): Automate infrastructure provisioning using tools like Ansible, Terraform etc.

- Monitoring and Logging: Set up monitoring tools such as Prometheus, Grafana and centralized logging (ELK stack or any other).

- Security Best Practices: Implement security policies, access controls, and vulnerability assessments.

- Collaboration: Work closely with cross-functional teams to align DevOps practices with business goals.

Mandatory Qualifications:

- Experience: Minimum of 3-5 years working with Kubernetes and Docker in a production environment.

- DevOps Skills: Strong understanding of DevOps principles, CI/CD, and infrastructure automation.

- Linux Proficiency: Comfortable with Linux system administration and scripting.

- Cloud Platforms: Familiarity with cloud platforms (e.g., GCP, Azure).

- Configuration Management: Knowledge of tools like Ansible, GHE.

- Certifications: Kubernetes certifications (CKA, CKAD) are a plus.

Desired Qualifications:

- Understanding of Machine Learning Deployments: Familiarity with deploying machine learning models and frameworks in production environments.

- Basic Understanding of Monitoring and Logging (Desirable): Familiarity with foundational concepts of monitoring system performance and logging activities for troubleshooting and analysis purposes.

- Exposure to monitoring tools like Prometheus, ELK stack (Elasticsearch, Logstash, Kibana), or similar platforms is advantageous.

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