Software Engineer, Applied AI

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.

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
• Create production-quality software for data pipelines for acquisition, model serving, monitoring, lifecycle management, data processing, and system integration
• Develop 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
• Manage time effectively across meetings, technical discovery, implementation, experimentation, and production support

Minimum Requirements

• BS/MS in Computer Science, Engineering, Machine Learning, Applied Mathematics, Physics, or a related technical field
• 2+ years of professional software development experience
• Strong Python programming skills
• Experience building, testing, deploying, and supporting production software systems
• 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

Preferred Qualifications

• Experience with analog or digital RF signal processing
• Experience with digital picture or 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 drone, robotics, sensor fusion, tracking, or moving-target detection systems
• Contributions to open-source projects or technically significant public work
• Familiarity with edge deployment, low-latency inference, hardware-constrained systems, or degraded-connectivity environments