Jobs at AeroVect

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.

Own and productionize localization, mapping, calibration, and state-estimation systems for autonomous ground vehicles operating at active airports. Responsibilities include sensor fusion, 3D mapping, calibration, online validation, diagnostics, regression testing, deployment, and safety monitoring. The role provides technical leadership across perception, planning, and platform teams while advancing autonomous operations toward driverless capability.

Designs and implements behavior planning algorithms for autonomous vehicles operating in structured, low-speed airport environments. Responsibilities include developing C++ and Python software, modeling multi-agent interactions, implementing decision-making and path-planning methods, testing in simulation and real-world scenarios, optimizing system performance, and collaborating with autonomy and engineering teams. The role requires expertise in behavior planning, probabilistic models, real-time navigation, debugging, profiling, and scalable software architecture.

Performs software and system safety analyses for autonomous vehicle platforms, including HARA, FMEA, FTA, STPA, freedom-from-interference, and code-level hazard evaluations. Derives and traces safety requirements, defines fail-safe mechanisms, reviews safety-critical C++ and Python code, supports safety-case development, and collaborates with robotics, hardware, systems, software, and test teams to verify compliance and enable airport deployment.

Design, build, and maintain cloud-based data pipelines and infrastructure on AWS, integrating on-prem and cloud flows. Implement IaC, CI/CD, containerization, observability, and automation to ensure high-throughput, reliable data ingestion and processing for autonomous systems.

Own and extend simulation tooling for autonomy: integrate simulators with the production autonomy stack, ensure determinism and reproducibility, run large-scale cloud scenario execution, build evaluation and triage tooling, author scenarios, and maintain pipeline performance and coverage for V&V and release gating.