We're looking for an experienced software engineer to start Chaos's practice of using AI to better build and test our systems. The ideal candidate has used machine learning and AI to make sense of complex hardware systems - whether that's automating root cause analysis in a production process, building perception pipelines for autonomous vehicles, using LLMs to interpret sensor telemetry, or deploying anomaly detection across IoT networks. You understand that physical systems are messy, complex, and high-stakes, and you know how to build AI workflows that deliver real-world results.

At CHAOS, you'll apply this skillset to cutting-edge sensing and defense systems — building AI-driven frameworks that validate, monitor, and diagnose hardware and software across radar, RF, and sensor fusion products.

Build AI-driven analysis pipelines for hardware-in-the-loop test systems - automated anomaly detection, root cause analysis, and regression identification across sensor and RF data

Design and deploy LLM-powered workflows that interpret system telemetry, summarize test results, and surface actionable insights from large volumes of sensor data

Develop end-to-end automated test and validation frameworks for software, firmware, and FPGA systems using Python, integrating into CI/CD pipelines

Create intelligent monitoring and reporting dashboards that go beyond pass/fail - using ML to identify drift, degradation, and subtle failure modes in physical systems

Work closely with systems engineers, hardware engineers, and software teams to close the loop between AI-driven insights and product improvements

Help establish and scale the team's testing and validation capabilities as a foundational member of the group

Work on-site in El Segundo, CA

AI Engineer, Physical Systems and Sensing

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Chaos Industries

More roles at Chaos Industries