AI/ML Engineer

Austin · Remotefull timeRemote

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Noda AI The AI/ML Engineer designs and implements intelligent agents for adaptive mission planning and orchestration across multi-domain unmanned systems. The role focuses on LLM orchestration frameworks, agent reasoning systems, and deploying AI models on edge computing hardware.

Responsibilities

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.
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 quantize 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
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-loop testing before field deployment
Design AI systems that maintain effectiveness in denied, degraded, and contested communication environments

Qualification

Experience with model optimizationFamiliarity with MLOps practicesKnowledge of prompt engineeringExperience with constraint solvingDue to the nature of the position

Required

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
Due to the nature of the position, U.S. citizenship is required due to ITAR regulations, along with the ability to obtain and maintain a DoD security clearance.

Preferred

Experience with multi-agent coordination frameworks and distributed AI reasoning systems
Background in robotics or autonomous systems integration (ROS2ROS 2, navigation stacks, sensor fusion)
Familiarity with reinforcement learning for planning and decision-making applications. Understanding; 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-loop and hardware-in-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