How to Put Docker/Kubernetes on Your Resume

Deployed and maintained production ML models serving 10M+ predictions daily across recommendation, search ranking, and fraud detection systems. P99 inference latency stays under 50ms using TorchServe on a Kubernetes cluster with auto-scaling based on request volume

Built the ML platform that serves 30+ production models with automated retraining triggers, A/B traffic splitting, and canary deployments with automatic rollback on metric degradation. The platform handles the full lifecycle from experiment to production without requiring data scientists to write deployment code

Designed and built a public REST API serving 2B requests per month for a SaaS platform with 5,000+ developer integrations, maintaining P99 latency under 150ms and 99.99% uptime over 18 months

Designed a multi-account AWS architecture using AWS Organizations with 15 accounts across production, staging, development, and security OUs, implementing SCPs and IAM policies that passed SOC 2 audit with zero findings

Built a two-stage recommendation system (candidate generation + ranking) serving 15M daily active users, increasing click-through rate by 23% and driving $12M in incremental annual revenue compared to the previous popularity-based approach.