AI/ ML Engineer – LLM/ Python/ Claude – Technology Company – Permanent + Bens – Austin, Texas

We are seeking an AI/ML Engineer to design and implement intelligent agents on behalf of our client. 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 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
• 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 (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
• Experience collaborating with security and compliance teams on logging, auditability, and data-handling requirements for fielded AI systems

What We Offer

• Hybrid work environment
• Competitive pay
• Flexible time off
• Generous PTO policy
• Federal holidays
• Generous health, dental, and vision benefits insurance
• Free OneMedical membership

How Do You Apply?

If you are interested in applying for the AI/ ML Engineer role, please do so via the link on this page or contact Digital Republic on the phone or by email

Get in contact with Digital Republic Talent by sending an email to [email protected]. Check out the website at www.digitalrepublictalent.com. You can also find out more on LinkedIn, Instagram or Facebook