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# AI Engineer, Physical Systems and Sensing

- **Company:** CHAOS Industries
- **Location:** El Segundo, CA, United States
- **Experience:** Expert
- **Salary:** $145,000.0 - $250,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Systems Engineering, Automation of Tests, Microsoft Azure, Code Generation, Nvidia CUDA, Continuous Integration, Firmware, Field-Programmable Gate Array (FPGA), Hardware-In-The-Loop Simulation, Python (Programming Language), Log Analysis, Machine Learning, Sensor Fusion, Signal Processing, Jupyter Notebook, Data Processing, Performance Testing, Large Language Models, Data Analytics, Real Time Data, Bitbucket, Machine Learning Operations, Data Pipelines, Automation Anywhere, Jenkins
- **Published:** July 28, 2026
- **Apply:** https://www.dice.com/job-detail/2267b0b3-e302-4e2e-b0a6-86b60da71705

## About the Role

5+ years of experience applying AI/ML to physical or IoT systems - e.g., manufacturing analytics, autonomous vehicles, robotics, sensor systems, industrial automation, or similar domains

 - Strong Python proficiency with hands-on experience building data pipelines and ML workflows (not just Jupyter notebooks - production systems)
 - Experience with real-world sensor data: time-series analysis, signal processing, anomaly detection, or similar
 - Familiarity with LLMs and AI tooling in engineering workflows (e.g., using LLMs for log analysis, code generation, root cause investigation)
 - Background working with hardware-in-the-loop systems, embedded systems, or real-time data streams
 - CI/CD experience (Jenkins, Azure, Bitbucket) and comfort with Dockerized/cloud-deployed environments
 - Ability to work cross-functionally with hardware and systems engineering teams - you can read a schematic, understand a test rack, and talk to an RF engineer

Nice to Have

 - Defense or aerospace domain experience (radar, RF/IQ data processing, sensor fusion)
 - Experience with CUDA, FPGA workflows, or GPU-accelerated computing
 - Background in autonomous systems, self-driving vehicles, or robotics perception pipelines
 - Performance testing, fault injection, or simulation-based validation
 - Experience scaling AI/ML systems from prototype to production in regulated environments

## Description

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.

What You'll Do

 - 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


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