Software Engineer, Sensing Systems

CHAOS Industries•El Segundo, CA

5d•$154,000 - $211,000•Onsite

About The Position

CHAOS Industries is hiring an early software engineer for its electro-optical team, initially focused on long-range EO/IR sensors and potentially expanding to sensors on mobile and airborne platforms. The role centers on building software that lets individual sensors and multi-sensor systems operate together. It is a software engineering position rather than an algorithm research, physics modeling, applied machine learning, or pure DevOps role. The engineer will work closely with physical systems, contribute to field testing, and debug and update software as it is tested on real hardware. The role also focuses on developing a software delivery and test path that progresses from simulation through hardware-in-the-loop testing to end-to-end tests on real hardware. This includes building the harnesses and workflow graphs that move capabilities through those stages, improving simulation and replay, and enabling autonomous tests at company test sites. AI tools are intended to assist this work where appropriate. The position is on-site in El Segundo, California, and includes regular travel to test sites and field deployments. U.S. Person status is required because the role requires access to U.S.-only data systems. The employee must be able to obtain and maintain a U.S. security clearance.

Requirements

At least 3 years of professional software engineering experience, including end-to-end ownership of a production system: designing, shipping, and fixing it.
Degree in Computer Science, Engineering, Physics, or a related field, or equivalent experience.
Strong Python skills, including building services and tools used by other engineers.
Comfort with Linux, Docker, networking, and CI, including bringing up a multi-service system on unfamiliar hardware.
Effective use of AI coding tools such as Cursor or Claude Code, with considered judgment about what to delegate; able to write, explain, and debug code without them.
Grounding in the physical world through an engineering degree, hands-on hardware, sensor or robotics work, or field experience with systems used outside the lab.
Ability to read a schematic, understand a test rack, and communicate with optics or RF engineers.
Interest in on-site field work and debugging and shipping fixes while systems are being tested.
Habit of measuring and validating system behavior with experiments rather than assumptions.
U.S. Person status, due to required access to U.S.-only data systems.
Ability to obtain and maintain a U.S. security clearance.
Willingness to work on-site in El Segundo, California, and travel regularly to test sites and field deployments.

Nice To Haves

Experience with cameras, EO/IR sensors, gimbals, radar, or video pipelines such as GStreamer or DeepStream.
Embedded Linux or edge computing experience, especially with NVIDIA Jetson.
GPU or CUDA experience.
Experience in robotics, autonomous vehicles, drones, or aerospace.
Experience with hardware-in-the-loop test rigs or test automation against real hardware.
Simulation or game-engine experience, such as Gazebo, Isaac Sim, or Unreal.
Experience building AI agent harnesses or workflow graphs.
C++ or TypeScript experience.
Defense or aerospace experience.
Current U.S. security clearance.

Responsibilities

Build generic, performant software that works across different sensor heads and configurations and can adapt to mission and customer needs.
Develop harnesses and workflow graphs that move capabilities from initial development through simulation and hardware-in-the-loop testing to end-to-end field tests with minimal manual effort.
Build systems that autonomously run complete tests against real hardware at test sites and report results.
Improve simulation and replay so more features can be developed and validated before hardware testing.
Build interfaces, timing, and data flows that integrate radar, cameras, and other sensors into one system.
Deploy, monitor, and live-fix software running on edge hardware at test and customer sites.
Participate in field testing, measure system behavior, debug issues, and deliver fixes before subsequent flights.
Use AI coding tools thoughtfully to support engineering work while retaining the ability to write, explain, and debug code independently.
Build and run experiments and rely on measured data to evaluate system behavior.