Software Engineer, Sensing Systems

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, and London. For more information, please visit  .

We're hiring one of the first software engineers on our electro-optical team. Today that means long-range EO/IR sensors. In future it could mean sensors on mobile and airborne platforms. Wherever the sensor sits, the job is the software that makes it, and every sensor around it, act as one system.

This is a software engineering role first. You don't need to be a camera or computer vision specialist. You do need to be an excellent engineer who is curious about physical systems and understands how real sensors behave: they drift, they disagree with each other, and a field test doesn't care what the simulation said.

You'll join a small, elite team that takes its own work into the field. You'll test live, change code live, and see how it holds up on the next flight. The capabilities you build will push the frontier of what these systems can do, and few engineers anywhere get to work this close to the hardware, the mission and the result.

We're also changing how we build software. The aim is to take a feature or a new capability and develop as much of it as possible without real hardware, then push it up the chain: through simulation, through hardware in the loop, and on to full end-to-end tests in the real world. Simulation will keep improving, but real hardware will always have the final say.

So we're building the harnesses and graphs that carry a capability through every one of those stages, with AI doing as much of the work as it can be trusted with. The end state is fully autonomous, end-to-end tests run against real hardware at our test sites. This is what you'll be building.

• Software that works on any sensor. Code that stays generic across many different camera heads and configurations while still hitting its performance bar, and flexes to whatever the mission and the customer demand.
• The path from desk to field. Harnesses and graphs that take a capability from first commit through simulation and hardware in the loop to a full end-to-end test, with as little manual effort as possible.
• Autonomous field testing. The system that runs complete tests against real hardware at our test sites on its own, and reports back what happened.
• Better simulation and replay. So more of every feature can be built and proven before it touches hardware.
• Multi-sensor integration. The interfaces, timing and data flow that let radar, cameras and other sensors work as one system.
• Fielded software. Deployment, monitoring and live fixes for systems running on edge hardware at test and customer sites.

• Algorithm research. You'll build and ship software, not invent new detection or tracking algorithms.
• Physics modeling. You won't be building high-fidelity physics models in MATLAB or Simulink.
• Applied machine learning. You won't be training models on sensor data.
• Pure Dev Ops. You'll run infrastructure, but most of your time goes into writing software other engineers depend on.

We care more about strong engineering fundamentals and curiosity than about any specific…