AI Engineer, Physical Systems and Sensing

Posted Yesterday
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El Segundo, CA, USA
In-Office
175K-241K Annually
Senior level
Hardware
The Role
Build AI-driven pipelines and automated validation frameworks for radar, RF, sensor, software, firmware, and FPGA systems. Develop anomaly detection, root cause analysis, LLM-powered telemetry interpretation, monitoring dashboards, and CI/CD-integrated testing workflows. Collaborate with hardware and systems engineers to improve defense and sensing products. The role requires production-grade Python, sensor-data expertise, hardware-in-the-loop experience, and on-site work in El Segundo, California.
Summary Generated by Built In

CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

The Role
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 
What We're Looking For
- 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


Why CHAOS?

  • Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
  • Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
  • Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
  • Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
  • Team Growth: 350 employees and counting across 5 global offices
Salary Range: $175,000 - $241,000

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 


Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

Skills Required

  • 5+ years applying AI or machine learning to physical or IoT systems
  • Strong Python proficiency and experience building production data pipelines and machine learning workflows
  • Experience with real-world sensor data, including time-series analysis, signal processing, or anomaly detection
  • Familiarity with LLMs and AI tooling in engineering workflows
  • Experience with hardware-in-the-loop systems, embedded systems, or real-time data streams
  • CI/CD experience with Jenkins, Azure, or Bitbucket
  • Experience with Dockerized or cloud-deployed environments
  • Ability to collaborate with hardware and systems engineering teams and understand schematics and test racks
  • Defense or aerospace experience, including radar, RF/IQ data processing, or sensor fusion
  • Experience with CUDA, FPGA workflows, or GPU-accelerated computing
  • Background in autonomous systems, self-driving vehicles, or robotics perception pipelines
  • Experience with performance testing, fault injection, or simulation-based validation
  • Experience scaling AI or machine learning systems from prototype to production in regulated environments
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The Company
HQ: Los Angeles, CA

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