Site Reliability Engineer (AWS & ML) - Remote

Employment type: Full-time | Day Shift

About the Role

This position operates within Japan's leading restaurant reservation and hospitality management platform, which currently powers operations globally. We run a robust and highly fault-tolerant enterprise infrastructure built entirely on Amazon Web Services (AWS) utilizing modern technologies like Terraform, Kubernetes (EKS), Helm, and automated CI/CD pipelines.

We operate in a highly collaborative, remote-first, and document-driven culture where team members are expected to take complete ownership of their domains.

Key Responsibilities

• 24/7 Production Stability: Maintain a highly available, scalable, and secure production environment on Kubernetes following standard SRE principles.
• DevOps Methodologies: Implement modern DevOps practices to consistently improve automated workflows and internal engineering quality of life.
• Infrastructure Management: Manage and scale core AWS cloud infrastructure services, specifically covering EKS, EC2, RDS, Fargate, CloudFront, Lambda, and S3.
• Infrastructure as Code (IaC): Build and maintain highly reusable infrastructure modules and CI/CD automation pipelines utilizing Terraform, Helm, and ArgoCD.
• Observability & Incident Response: Proactively monitor systems, configure alerts, and lead high-efficiency incident response and technical postmortem processes.

• ML Infrastructure Operations: Apply rigid SRE discipline to our machine learning stack—ensuring model serving, training pipelines, and data layers remain observable, stable, and highly performant.
• Model Deployment Pipelines: Support and continuously optimize ML model deployment pipelines and automated MLOps lifecycles.
• Collaborative Engineering: Partner closely with data science teams and core product tracks to operationalize machine learning models cleanly at an enterprise scale.
• EKS Optimization for ML: Deploy and optimize hardware-efficient infrastructure configurations tailored specifically for ML workloads on AWS Kubernetes.

• Cloud Experience: At least 2+ years of professional, hands-on experience managing Amazon Web Services (AWS) environments, with strong production exposure to EKS, EC2, RDS, Fargate, CloudFront, Lambda, and S3.
• EKS Expertise: Heavy, practical experience directly configuring and running workloads on AWS Elastic Kubernetes Service (EKS).
• SRE Leadership: Proven experience in software engineering following DevOps or SRE methodologies, including at least 1 year of experience acting as a technical lead.
• Programming Skills: Strong, active coding proficiency in at least one of the following languages: Python, Ruby, Elixir, Go, JavaScript, or Rust.
• Systems Foundations: Excellent understanding of containerization (Docker) and basic hypervisor and virtualization fundamentals.
• Automation Tooling: Solid knowledge of configuration management using YAML or Bash scripting; direct experience utilizing Helm and Terraform is highly preferred.
• ML/MLOps Familiarity: Conceptual familiarity with modern machine learning workflows, alongside hands-on Python experience using ML-adjacent tooling (e.g., model deployment pipelines or inference serving).

RH-TT