CHAOS Industries · San Francisco, CA, United States
Skills: React, TypeScript, Python
CHAOS Industries is redefining modern defense with omniscient systems purpose-built for today's realities. Designed and built by top U.S. military veterans and Silicon Valley innovators, CHAOS Industries' 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. In a world where technological threats move at unprecedented speed, CHAOS Industries delivers advanced sensing and detection solutions that give the ultimate advantage: time.
CHAOS Industries was founded in 2022 and has raised $1B in total funding from leading investors including 8VC, Accel, and NEA. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, and London. For more information, please visit www.chaosinc.com.
The Role
You'll join a small, highly collaborative team in San Francisco building the software behind some of the world's most advanced radar systems. Working alongside software, hardware, and systems engineers, and the teams who take these systems into the field, you'll design the backend services and data pipelines that turn raw sensor data into decisions people can act on. We're looking for builders who learn quickly and enjoy hard distributed systems and real-time data problems.
What You'll Build
Edge-to-Cloud Data Delivery - robust, low-latency systems that move sensor data from radars in the field, often over constrained bandwidth, to the services and operators that depend on it. Backend Services - high-performance Python (FastAPI) services that ingest, process, and distribute real-time sensor data reliably and securely at scale. Live and Replay Data - the streaming, storage, and replay of detections, tracks, and telemetry that power high-speed live views and playback of 3D geospatial data fused from multiple sensors. Fleet Orchestration - the coordination and decision-making layer that optimizes how …truncate…
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