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.
Role Overview:
- Support the Systems Engineering design and development of cutting-edge radar capabilities
Responsibilities:
- Design and develop advanced radar signal processing algorithms for target detection, tracking, and classification
- Lead the development of new radar capabilities with minimal guidance
- Optimize algorithms for real-time performance and resource constraints
- Implement algorithms in software (e.g., C++, Python, MATLAB) and/or hardware (e.g., FPGAs, DSPs)
- Analyze radar data to evaluate system performance and identify areas for improvement
- Develop and maintain system simulations and models to support algorithm development and performance evaluation.
- Design and development of radar modes
- Contribute to the development of system requirements and specifications
- Modeling and Simulation of radar systems and sub-systems as well as the signal processing chain
- Plan and lead field tests and data collection activities
- Document and present technical findings and progress to leadership
- Mentor and guide junior engineers
- Work full-time onsite at our office in El Segundo, CA
Minimum qualifications:
- Bachelor’s degree in STEM (Science, Technology, Engineering or Mathematics) or another related field or equivalent work experience
- Deep understanding of radar systems and modes
- Strong understanding of radar principles, signal processing techniques, and algorithms
