The Role
Build, integrate, evaluate, and deploy production AI/ML systems across defense product lines. Responsibilities include model serving, data pipelines, inference, monitoring, lifecycle management, robustness testing, interpretability, performance optimization, and edge deployment in constrained or adversarial environments. Collaborate with data scientists, software engineers, product teams, and mission stakeholders to turn research and prototypes into reliable software. The role requires strong Python and production engineering skills, with 10–20% travel and regular on-site work in San Francisco.
Summary Generated by Built In
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
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.
#LI-onsite
Skills Required
- US citizenship or permanent resident status
- Bachelor’s, master’s, or doctoral degree in computer science, electrical/electronics engineering, data science, applied mathematics, physics, a related technical field, or equivalent experience
- 2–5 years of professional software development experience; exceptional fresh graduates may apply
- Very strong Python programming skills
- Experience 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, edge deployment environments, or GPU optimization
- Ability and enthusiasm to learn unfamiliar technical domains
- Experience with explainable AI, including integrated gradients, counterfactuals, or occlusion methods
- Experience with real-time 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
- Experience with analog or digital RF signal processing
- 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
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The Company
