Asks for

The ad says“Experience with AI/ML model integration, model serving infrastructure, or model lifecycle management”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Experience with model evaluation, benchmarking, robustness testing, interpretability, or ML observability”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Experience with model evaluation, benchmarking, robustness testing, interpretability, or ML observability”
The ad says“Experience with model evaluation, benchmarking, robustness testing, interpretability, or ML observability”
The ad says“Experience with model evaluation, benchmarking, robustness testing, interpretability, or ML observability”
The ad says“Experience with AI/ML model integration, model serving infrastructure, or model lifecycle management”
The ad says“Experience with AI/ML model integration, model serving infrastructure, or model lifecycle management”
The ad says“Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization”
The ad says“Very strong Python programming skills”
The ad says“Experience with model evaluation, benchmarking, robustness testing, interpretability, or ML observability”

Values

The ad says“Experience building AI agents or agentic workflows”
The ad says“Experience building AI agents or agentic workflows”
The ad says“Any experience with analog or digital RF signal processing”
The ad says“Experience productizing machine learning models, LLM applications, computer vision systems, signal-processing systems, or autonomous/robotic systems.”
The ad says“Experience productizing machine learning models, LLM applications, computer vision systems, signal-processing systems, or autonomous/robotic systems.”
The ad says“Familiarity with edge deployment of in-data-path models, low-latency inference, hardware-constrained systems, or degraded-connectivity environments”
The ad says“Any experience with drones, sensor fusion, tracking, or moving-target detection systems”
The ad says“Familiarity with edge deployment of in-data-path models, low-latency inference, hardware-constrained systems, or degraded-connectivity environments”
The ad says“Experience with explainable AI (IG, Counterfactuals, Occlusion etc)”
The ad says“Familiarity with edge deployment of in-data-path models, low-latency inference, hardware-constrained systems, or degraded-connectivity environments”
The ad says“Experience productizing machine learning models, LLM applications, computer vision systems, signal-processing systems, or autonomous/robotic systems.”
The ad says“Familiarity with edge deployment of in-data-path models, low-latency inference, hardware-constrained systems, or degraded-connectivity environments”
The ad says“Experience productizing machine learning models, LLM applications, computer vision systems, signal-processing systems, or autonomous/robotic systems.”
The ad says“Any experience with drones, sensor fusion, tracking, or moving-target detection systems”
The ad says“Any experience with realtime digital video processing”
The ad says“Any experience with drones, sensor fusion, tracking, or moving-target detection systems”
The ad says“Experience productizing machine learning models, LLM applications, computer vision systems, signal-processing systems, or autonomous/robotic systems.”
The ad says“Any experience with drones, sensor fusion, tracking, or moving-target detection systems”

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

CHAOS is seeking a highly motivated, mission-oriented Applied AI Engineer to help develop, integrate, and deploy AI/ML-powered capabilities across our product lines.

In this role, you will work closely with other data scientists, software engineers, product teams, and mission stakeholders to conduct advanced AI research and turn them into reliable, real-world software. The work will focus especially on defense applications where the systems must perform with extreme accuracy under constrained, adversarial, and operationally complex conditions.

We are looking for someone with strong data science and software engineering fundamentals, a record of technical excellence, and demonstrated experience applying AI/ML techniques to real products. Experience in aerospace, defense, critical infrastructure, robotics, RF systems, or other highly regulated or mission-driven environments is a strong plus.

You should be comfortable operating with independence, learning unfamiliar technical domains quickly, working across disparate teams, and moving prototypes toward production with limited oversight.

Responsibilities

Build applied AI systems across CHAOS product lines, including model integration, inference services, evaluation pipelines, and production-facing AI capabilities
Perform research and build products by working with product and mission teams to research, collect data, verify hypothesis and create 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 pipelines for acquisition, model serving, monitoring, lifecycle management, data processing, and system integration.
Create rapid prototypes with mission and product teams, other relevant stakeholders and iterate toward production-ready implementations.
Contribute to AI system reliability, by conducting testing, benchmarking, observability, interpretability, failure analysis, and performance optimization.
Learn quickly from existing codebases, documentation, research artifacts, and domain experts, then use that knowledge to drive execution.
Manage time effectively across meetings, technical discovery, implementation, experimentation, and production support.
Travel: 10-20%.
Location: Must work on-site at least 2 days per week from our San Francisco office; 2–4 days per week preferred.

Minimum Requirements

US Citizen or Permanent Resident
BS/MS/PhD in Computer Science, Electrical/Electronics Engineering, Data Science, Applied Mathematics, Physics, or a related technical field or equivalent experience
2-5 years of professional software development experience (exceptional fresh grads welcome to apply)
Very strong Python programming skills
Experience in building, testing, deploying, and supporting production software and models
Experience with AI/ML model integration, model serving infrastructure, or model lifecycle management
Experience with model evaluation, benchmarking, robustness testing, interpretability, or ML observability
Familiarity with APIs, Distributed systems, Containers, CI/CD, observability, and edge deployment environments/GPU optimization
Excited to learn unfamiliar technical domains

Preferred Qualifications

Experience with explainable AI (IG, Counterfactuals, Occlusion etc)
Any experience with realtime digital video processing
Experience productizing machine learning models, LLM applications, computer vision systems, signal-processing systems, or autonomous/robotic systems.
Experience building AI agents or agentic workflows
Any experience with analog or digital RF signal processing
Any experience with drones, sensor fusion, tracking, or moving-target detection systems
Familiarity with edge deployment of in-data-path models, low-latency inference, hardware-constrained systems, or degraded-connectivity environments
Experience in aerospace, defense, critical infrastructure, robotics, or other mission-critical environments is a strong plus

Why CHAOS?

Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
Team Growth: 250 employees and counting across 5 global offices

$150k-170k

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations.

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

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