present of AI

The role is about building the internal platform that lets robotics engineers run large batches of simulation and automated tests without handling infrastructure themselves. A strong candidate has run cloud or developer platforms in production, knows Kubernetes, containers and CI/CD well, and can design job scheduling and orchestration that copes with failures. Writing clean Python or C++ and shaping simple tools and APIs for other engineers matters just as much.

How it fits the AI era

Simulation is a key way to test autonomous systems, and AI-driven software for vehicles needs a lot of repeatable virtual testing, so a platform like this becomes more valuable as autonomy grows. Automation can help with job scheduling, log analysis and spotting regressions. Judgment about what to test, how to keep results trustworthy, and how to make the platform dependable for colleagues stays with people.

How it builds AI experience

Working here would mean supporting the testing of autonomy software for unmanned ground vehicles, including GPU-heavy workloads and ROS2-based setups. Someone preparing for it could learn ROS2 with an open source simulator, run GPU jobs on a Kubernetes cluster, and try a small pipeline that replays scenarios and flags regressions in CI.

Worth showing

• Kubernetes and cloud platform operations
• CI/CD regression pipelines
• Python or C++ tooling
• ROS2 and simulation experience

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About ARX Robotics

ARX Robotics manufactures autonomous unmanned ground vehicles and defense software systems for military reconnaissance and transport operations.