# AI/ML Engineer

**Company:** [NODA AI](https://hotfix.jobs/companies/noda-ai)
**Location:** Austin, TX
**Role:** ML Engineering
**Experience:** 3+ years
**Skills:** Python, PyTorch, Transformers, LangChain, Ros 2, MLOps, LLMs, Prompt Engineering, Model Optimization, Quantization, Jetson, Kubernetes
**Posted:** 2025-11-13

> Designs and implements LLM orchestration frameworks and agent reasoning systems for adaptive mission planning in multi-domain unmanned systems. Optimizes AI models for edge deployment on autonomous vehicles, integrating with ROS autonomy stack for mission-critical operations.

## Job Description

## 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 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

## 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 (ROS 2, 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-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
- 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

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**Canonical:** https://hotfix.jobs/jobs/67cf0236-0062-4de7-bb06-6db351ef2f09