Senior SRE / MLOps Platform Engineer - Remote

Location: Metro Manila, Philippines | Remote

Employment type: Full-time | Day Shift

Senior SRE / MLOps Platform Engineer

Role Overview

We are seeking a Senior SRE / MLOps Platform Engineer to manage, scale, and evolve our production infrastructure on AWS and Kubernetes while bridging the gap between traditional SRE and Machine Learning operations. In this role, you will bring SRE discipline to our machine learning ecosystem—ensuring that model training pipelines, inference engines, and data workflows are resilient, observable, and highly scalable.

Key Responsibilities

• Production Infrastructure & SRE: Enforce SRE principles to maintain high availability and reliability for our 24/7 Kubernetes-based production environment.
• AWS Cloud Engineering: Manage and evolve core AWS infrastructure, focusing heavily on EKS, EC2, RDS, Fargate, CloudFront, Lambda, and S3.
• ML Infrastructure & MLOps: Apply SRE practices to ML platforms—ensuring model serving, training pipelines, and feature stores are reliable, scalable, and observable in production.
• Infrastructure as Code & CI/CD: Build, maintain, and optimize deployment pipelines and IaC frameworks using Terraform, Helm, and ArgoCD.
• Observability & Model Monitoring: Establish robust telemetry, alerting, and observability stack to track both infrastructure health and ML model performance in real time.
• Cross-Functional Enablement: Partner with Data Scientists, ML Engineers, and Product Teams to operationalize complex ML models and streamline deployment workflows.

Key Qualifications

Core Requirements

• Senior Experience & Technical Leadership: 5+ years of hands-on experience in SRE, DevOps, or Cloud Platform Engineering, including at least 1 year serving as a technical lead or senior mentor.
• AWS & Kubernetes Mastery: Deep, hands-on experience deploying and managing large-scale production workloads on AWS EKS, supported by core AWS services (EC2, RDS, Fargate, S3, CloudFront, Lambda).
• Programming & Automation: Strong software engineering background with current proficiency in Python, Go, or equivalent backend languages (Ruby, Elixir, JavaScript, Rust).
• IaC & Configuration: Advanced knowledge of containerization, distribution systems, and configuration management using Terraform, Helm, Bash, and YAML.
• MLOps & Pipeline Exposure: Hands-on familiarity with machine learning workflows, Python ML tooling, and model deployment/inference patterns on Kubernetes.

IT Talent Partner - RH