NODA AI
Overview
AI/ML Engineer role at NODA AI. Location: Austin, TX (Hybrid on-site, with up to 20% travel). Clearance Requirement: U.S. Citizen with the ability to obtain a security clearance. NODA is a veteran-owned, venture-backed technology company transforming how unmanned systems collaborate in complex, mission-critical environments. We enable autonomous orchestration of heterogeneous unmanned systems across air, sea, land, and space with vital applications in the defense, intelligence, and commercial sectors. Our AI/ML Engineers design and implement AI agents that bridge mission intent with real-world execution through advanced reasoning frameworks and multi-domain orchestration capabilities. Joining NODA means working on meaningful technology that pushes the boundaries of autonomy alongside a team that thrives on innovation, rapid iteration, and collaboration. The Role
We are seeking an AI/ML Engineer to design and implement intelligent agents that drive adaptive mission planning and orchestration across multi-domain unmanned systems. This role focuses on LLM orchestration frameworks, agent reasoning systems, and the deployment of AI models to edge computing environments on autonomous vehicles. You will build systems that translate high-level mission intent into actionable autonomous behaviors, dynamically adapt plans as environments change, and provide explainable reasoning to human operators. Your work will integrate directly with our ROS autonomy stack while ensuring reliable AI performance on resource-constrained edge hardware. Key Responsibilities
Design and implement LLM orchestration frameworks for mission planning and task decomposition across heterogeneous vehicle fleets Develop agent reasoning systems that bridge high-level mission objectives with executable autonomy commands Optimize large and quantized language models and agent frameworks for deployment on edge computing hardware (Jetson, companion computers) Manage the full lifecycle of AI agents including model versioning, prompt engineering, tool integration, and memory management Implement human-in-the-loop workflows that provide transparent, explainable AI reasoning to operators Integrate AI reasoning outputs with autonomy middleware (e.g., ROS 2) to enable seamless mission execution across heterogeneous platforms Build evaluation, monitoring, and logging systems to track agent performance, reliability, and cost in operational environments Develop safe deployment and rollback practices for AI agents in mission-critical scenarios Collaborate with autonomy engineers to ensure AI-generated plans are executable and safe across multi-domain platforms Validate agent behaviors through simulation-in-the-loop testing before field deployment Design AI systems that maintain effectiveness in denied, degraded, and contested communication environments Required Qualifications
3+ years of experience in production AI/ML applications with emphasis on LLM deployment and orchestration Proficiency in Python and modern AI/ML frameworks (PyTorch, Transformers, LangChain, or equivalent orchestration tools) Experience with model optimization, quantization, and deployment to edge computing environments Understanding of distributed systems and real-time AI inference requirements Familiarity with MLOps practices, including model versioning, monitoring, and lifecycle management Knowledge of prompt engineering, agent framework design, and multi-step reasoning systems Experience with constraint solving, planning algorithms, or symbolic reasoning approaches U.S. Citizenship with the ability to obtain a security clearance Preferred Qualifications
Experience with multi-agent coordination frameworks and distributed AI reasoning systems Background in robotics or autonomous systems integration (ROS2, navigation stacks, sensor fusion) Familiarity with reinforcement learning for planning and decision-making applications; understanding of secure coding practices and adversarial robustness in AI-driven systems Experience deploying AI models to embedded hardware (Jetson, Raspberry Pi, or similar edge devices) Exposure to simulation-in-the-loop and hardware-in-the-loop testing environments Knowledge of autonomous vehicle domains (UAVs, USVs, UUVs) and associated protocols Background in structured data preparation and feature engineering for AI ingestion Contributions to open-source AI or robotics projects Experience contributing to mission assurance and safety cases, including field-readiness reviews Experience collaborating with security and compliance teams on logging, auditability, and data-handling requirements for fielded AI systems Skills and Attributes
Systems thinker able to connect AI reasoning outputs with real-world autonomous execution Fast learner with adaptability to rapidly evolving AI/ML frameworks and methodologies Safety-focused mindset with commitment to explainable, reliable AI in mission-critical environments Thrives in ambiguous, mission-driven problem spaces requiring creative AI solutions Collaborative team player across AI, autonomy, and field operations disciplines Detail-oriented approach to AI system validation, testing, and performance optimization What We Offer
Hybrid work environment Competitive pay Flexible time off Generous PTO policy Federal holidays Generous health, dental, and vision benefits Free OneMedical membership Growth Path at NODA
AI/ML Engineer → Senior AI/ML Engineer → Staff AI/ML Engineer → Principal Engineer. Final leveling will be determined at the offer stage based on scope demonstrated in interviews, prior impact, and calibration to NODA’s career ladder. We are an Equal Opportunity Employer and welcome applicants from all backgrounds. All qualified individuals will receive consideration for employment regardless of race, age, color, religion, sex, national origin, disability, or protected veteran status.
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AI/ML Engineer role at NODA AI. Location: Austin, TX (Hybrid on-site, with up to 20% travel). Clearance Requirement: U.S. Citizen with the ability to obtain a security clearance. NODA is a veteran-owned, venture-backed technology company transforming how unmanned systems collaborate in complex, mission-critical environments. We enable autonomous orchestration of heterogeneous unmanned systems across air, sea, land, and space with vital applications in the defense, intelligence, and commercial sectors. Our AI/ML Engineers design and implement AI agents that bridge mission intent with real-world execution through advanced reasoning frameworks and multi-domain orchestration capabilities. Joining NODA means working on meaningful technology that pushes the boundaries of autonomy alongside a team that thrives on innovation, rapid iteration, and collaboration. The Role
We are seeking an AI/ML Engineer to design and implement intelligent agents that drive adaptive mission planning and orchestration across multi-domain unmanned systems. This role focuses on LLM orchestration frameworks, agent reasoning systems, and the deployment of AI models to edge computing environments on autonomous vehicles. You will build systems that translate high-level mission intent into actionable autonomous behaviors, dynamically adapt plans as environments change, and provide explainable reasoning to human operators. Your work will integrate directly with our ROS autonomy stack while ensuring reliable AI performance on resource-constrained edge hardware. Key Responsibilities
Design and implement LLM orchestration frameworks for mission planning and task decomposition across heterogeneous vehicle fleets Develop agent reasoning systems that bridge high-level mission objectives with executable autonomy commands Optimize large and quantized language models and agent frameworks for deployment on edge computing hardware (Jetson, companion computers) Manage the full lifecycle of AI agents including model versioning, prompt engineering, tool integration, and memory management Implement human-in-the-loop workflows that provide transparent, explainable AI reasoning to operators Integrate AI reasoning outputs with autonomy middleware (e.g., ROS 2) to enable seamless mission execution across heterogeneous platforms Build evaluation, monitoring, and logging systems to track agent performance, reliability, and cost in operational environments Develop safe deployment and rollback practices for AI agents in mission-critical scenarios Collaborate with autonomy engineers to ensure AI-generated plans are executable and safe across multi-domain platforms Validate agent behaviors through simulation-in-the-loop testing before field deployment Design AI systems that maintain effectiveness in denied, degraded, and contested communication environments Required Qualifications
3+ years of experience in production AI/ML applications with emphasis on LLM deployment and orchestration Proficiency in Python and modern AI/ML frameworks (PyTorch, Transformers, LangChain, or equivalent orchestration tools) Experience with model optimization, quantization, and deployment to edge computing environments Understanding of distributed systems and real-time AI inference requirements Familiarity with MLOps practices, including model versioning, monitoring, and lifecycle management Knowledge of prompt engineering, agent framework design, and multi-step reasoning systems Experience with constraint solving, planning algorithms, or symbolic reasoning approaches U.S. Citizenship with the ability to obtain a security clearance Preferred Qualifications
Experience with multi-agent coordination frameworks and distributed AI reasoning systems Background in robotics or autonomous systems integration (ROS2, navigation stacks, sensor fusion) Familiarity with reinforcement learning for planning and decision-making applications; understanding of secure coding practices and adversarial robustness in AI-driven systems Experience deploying AI models to embedded hardware (Jetson, Raspberry Pi, or similar edge devices) Exposure to simulation-in-the-loop and hardware-in-the-loop testing environments Knowledge of autonomous vehicle domains (UAVs, USVs, UUVs) and associated protocols Background in structured data preparation and feature engineering for AI ingestion Contributions to open-source AI or robotics projects Experience contributing to mission assurance and safety cases, including field-readiness reviews Experience collaborating with security and compliance teams on logging, auditability, and data-handling requirements for fielded AI systems Skills and Attributes
Systems thinker able to connect AI reasoning outputs with real-world autonomous execution Fast learner with adaptability to rapidly evolving AI/ML frameworks and methodologies Safety-focused mindset with commitment to explainable, reliable AI in mission-critical environments Thrives in ambiguous, mission-driven problem spaces requiring creative AI solutions Collaborative team player across AI, autonomy, and field operations disciplines Detail-oriented approach to AI system validation, testing, and performance optimization What We Offer
Hybrid work environment Competitive pay Flexible time off Generous PTO policy Federal holidays Generous health, dental, and vision benefits Free OneMedical membership Growth Path at NODA
AI/ML Engineer → Senior AI/ML Engineer → Staff AI/ML Engineer → Principal Engineer. Final leveling will be determined at the offer stage based on scope demonstrated in interviews, prior impact, and calibration to NODA’s career ladder. We are an Equal Opportunity Employer and welcome applicants from all backgrounds. All qualified individuals will receive consideration for employment regardless of race, age, color, religion, sex, national origin, disability, or protected veteran status.
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