AeroVect Benefits Overview

Designs and implements behavior planning systems for autonomous vehicles operating in structured, low-speed airport environments. Develops planning algorithms, decision-making modules, and scalable C++ and Python software; tests in simulation and real-world scenarios; optimizes performance and latency; and collaborates with autonomy and engineering teams. The role involves multi-agent interaction modeling, state machines, behavior trees, probabilistic planning, path planning, dynamic replanning, documentation, and system integration.

Architect and deploy multimodal 2D/3D object detection systems using camera, LiDAR, and radar. Build data collection, evaluation, and proprietary dataset pipelines; train, monitor, and improve production perception models; develop the perception roadmap; and mentor junior engineers. The role requires end-to-end perception stack experience, cross-functional leadership, Python proficiency, and advanced education in computer science, robotics, or deep learning.

Design and build production-grade mission, behavior, and motion planning systems for autonomous ground-support vehicles in airport environments. Responsibilities include selecting planning algorithms, architecting software interfaces, optimizing trajectories, addressing uncertainty and real-time constraints, collaborating with perception and controls teams, applying safety practices, and mentoring engineers. The role requires strong C++ or Python skills, Linux experience, and hands-on autonomous systems planning experience.