Software Engineer, Numerical Computing

About the role

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 www.chaosinc.com.

Role Overview:

We are seeking a software engineer who is fluent in numerical computing to build the software foundation of our electromagnetic warfare product line. Our Spectrum Sensing team is transforming CHAOS radar systems into distributed sensing systems that detect, classify, and geolocate RF emissions — and the algorithms that do it only matter if they run correctly, quickly, and reliably in production.

This is a software engineering role first. You will own how our numerical and signal processing code is architected, integrated, tested, and accelerated. You do not need a background in RF or radar; you do need to be the person on the team who knows why a Python implementation is slow, what to do about it, and how to build a codebase that other engineers can safely extend. You will work alongside signal processing and RF engineers who supply the algorithms, and you will be the reason those algorithms become dependable software.

Responsibilities:

As a key contributor to the Spectrum Sensing team, you will shape the software architecture and engineering practices behind our sensing stack. The day-to-day will be diverse, engaging, and intellectually stimulating, with direct impact on pushing the boundaries of sensing technology and application. Key responsibilities include:

- Design, develop, and maintain production-quality numerical software in Python, with an emphasis on clear interfaces, composability, and long-term maintainability

- Integrate third-party software and hardware into the CHAOS platform via APIs, and own the abstractions that keep those integrations from leaking into the rest of the codebase

- Profile and accelerate signal processing implementations — through vectorization, array-programming frameworks, JIT compilation, GPU offload, or bindings to compiled code — and quantify the improvement

- Define and drive test and CI hygiene for numerical code: numerical regression tests, tolerance and reproducibility strategy, property-based and reference-implementation testing, and automation that catches breakage before a field demonstration does

- Partner with signal processing engineers to turn algorithms from papers, prototypes, and MATLAB into software that ships

- Contribute to overall software architecture decisions for the sensing product line, including how components compose across the platform