Senior RL & Autonomous Decision Systems Engineer

Aurex; Huntsville (AL); On-site; USD 170,000 - 200,000; Full time

Job summary

Aurex is seeking a Senior Reinforcement Learning / AI Engineer to develop RL-enabled decision systems for aerospace and defense. You will create intelligent agents for closed-loop decision making in simulated and real-time environments, addressing continuous, discrete, and hybrid decision spaces.

The role emphasizes sequential decision-making, autonomous behavior, and rigorous evaluation, with collaboration across modeling, software, and systems teams.

Qualifications

• Bachelor’s degree or higher in a technical field and 10+ years in RL/autonomy or related engineering disciplines.
• Hands-on experience developing, training, and evaluating RL agents for sequential decision‑making, planning, control, or autonomous systems.
• Strong Python software development experience and familiarity with modern DL frameworks (PyTorch, TensorFlow, etc.).

Responsibilities

• Design, train, and evaluate reinforcement-learning agents for mission planning, guidance, and control.
• Translate operational problems into rigorous sequential-decision formulations.
• Build simulation-based learning environments connecting agents to models and sensors.
• Develop end-to-end training workflows with scenario generation and experiment tracking.
• Provide technical leadership and mentorship to engineers.

Skills

Python

Reinforcement learning

Simulation environments

Git / CI/CD

Communication

Team leadership

Education

Bachelor’s degree in Computer Science or related field

Master’s degree or PhD in related field

Tools

Ray/RLlib

Stable-Baselines3

Docker

Linux

PyTorch

Job description

Aurex is seeking a Senior Reinforcement Learning / AI Engineer to develop RL-enabled decision systems for aerospace and defense. You will create intelligent agents for closed-loop decision making in simulated and real-time environments, addressing continuous, discrete, and hybrid decision spaces.

The role emphasizes sequential decision-making, autonomous behavior, and rigorous evaluation, with collaboration across modeling, software, and systems teams.