Josef Doornink

Machine Learning Systems Engineer

10+ years building high-performance distributed systems • Focusing on MLOps infrastructure and large-scale Kubernetes environments

— MLOps Engineer — Building production ML infrastructure for model training, serving, and monitoring at scale

— Performance Optimization — Profiling distributed systems, eliminating bottlenecks, and improving throughput

— Developer Tools — Creating automation tools that dramatically improve team productivity

— Cloud Architecture — CKS/CKA certified with deep expertise in Kubernetes, Azure, and Infrastructure as Code

— Passionate about AI — Committed to building reliable, scalable systems that enable breakthrough ML research

Key Projects

Distributed Training Pipeline Optimization

Reason Benefit AI | 2025

Profiled reinforcement learning training pipeline to identify critical performance bottlenecks
Implemented microservice architecture to deliver UI focused MLOps services
Built automated test environment for continuous pipeline health validation
Significantly reduced training time through systematic performance optimization

Python RL Profiling

Kubernetes Security Hardening Initiative

Trimble/Viewpoint | 2024

Implemented CKS best practices across production Kubernetes clusters
Achieved SOC2 compliance through systematic security improvements
Designed automated security scanning and remediation workflows
Significantly reduced vulnerabilities through continuous monitoring

Kubernetes Security Python

High-Performance CLI Tooling

Trimble/Viewpoint | 2023

Created production-grade CLI tools in Go using Cobra framework
Implemented features for service discovery, log aggregation, and deployment automation
Tools adopted by 50+ engineers across the organization
Significantly improved operational efficiency and developer experience

Go CLI DevOps

Portfolio

SKILLS

RESUME

GITHUB

PATENTS & AWARDS

PUBLICATIONS

CERTIFICATIONS