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CHAOS Industries

Develops military sensor and radar systems

Applied AI Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • A Bachelor of Science or Master of Science degree in Computer Science, Engineering, Machine Learning, Applied Mathematics, Physics, or a related technical field.
  • At least 2 years of professional software development experience.
  • Strong Python programming skills.
  • Experience building, testing, deploying, and supporting production software systems.
  • Experience with artificial intelligence and machine learning model integration, model serving infrastructure, or model lifecycle management.
  • Experience with model evaluation, benchmarking, robustness testing, interpretability, or machine learning observability.
  • Familiarity with application programming interfaces, distributed systems, containers, continuous integration and continuous delivery, observability, edge deployment environments, and graphics processing unit optimization.

Responsibilities

  • Build applied artificial intelligence systems across product lines, including model integration, inference services, evaluation pipelines, and production-facing AI capabilities.
  • Conduct research and build products with product and mission teams by collecting data, verifying hypotheses, and creating robust, testable, maintainable, and deployable models.
  • Evaluate and improve model performance under real-world conditions, including adversarial GPS-denied environments, low-power or edge deployments, and degraded or noisy inputs.
  • Develop production-quality software for data acquisition pipelines, model serving, monitoring, lifecycle management, data processing, and system integration.
  • Create rapid prototypes with mission and product teams and other stakeholders, then iterate toward production-ready implementations.
  • Improve AI system reliability through testing, benchmarking, observability, interpretability, failure analysis, and performance optimization.
  • Learn from existing codebases, documentation, research artifacts, and domain experts, then use that knowledge to drive execution.
  • Manage time across meetings, technical discovery, implementation, experimentation, and production support.

Desired Qualifications

  • Experience with analog or digital radio-frequency signal processing.
  • Experience with digital picture or video processing.
  • Experience productizing machine learning models, large language model applications, computer vision systems, signal-processing systems, or autonomous and robotic systems.
  • Experience building AI agents or agentic workflows.
  • Experience with drones, robotics, sensor fusion, tracking, or moving-target detection systems.
  • Contributions to open-source projects or technically significant public work.
  • Experience in aerospace, defense, critical infrastructure, robotics, or other mission-critical environments.
  • Familiarity with edge deployment, low-latency inference, hardware-constrained systems, or degraded-connectivity environments.

About the Company

CHAOS Industries

Develops military sensor and radar systems

Chaos Industries builds defense technology by creating sensor, radar, and network systems for military and security use. Its Coherent Distributed Networks (CDN) synchronizes a network of sensors to improve detection and situational awareness across land, sea, and air, enabling earlier threat warnings. Its product line includes Vanquish multistatic radar for early warning and tracking of unmanned systems and missiles, the HYDRA software-defined platform for detection and communications, and ASTRIA for long-range mobile multi-object tracking; it has formed an Aerospace Division after acquiring Ziva Corporation and Atropos Group. The company targets U.S. and allied defense clients, focusing on software-driven systems that can be updated and deployed quickly, with the goal of delivering faster reactions and better national security readiness while expanding production and advancing its technology roadmap.

Company size
201-500
Company stage
Series D
Total funding
$1B
Headquarters
Los Angeles, CA
Founded
2022

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