Principal Engineer, Autonomy
AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers operate. Backed by top-tier venture capital, we serve some of the world’s largest airlines and ground handling providers. Learn more at www.aerovect.com.
About the role
We are hiring a Principal Engineer for Autonomy, the senior-most individual contributor in our autonomy organization. Reporting directly to the VP of Engineering, you will have deep technical ownership of one or more of Perception, Prediction, and Planning, influencing the entire stack.
Responsibilities
Own the design and evolution of the perception stack — detection, classification, tracking, and multi-modal sensor fusion across available modalities.
Drive perception robustness across real-world operating conditions and set the direction for deep learning applications.
Own the prediction stack and models for intent inference, behavior forecasting, and handling occlusions and edge cases.
Set the direction for prediction integration with perception and planning.
Own the planning and decision-making stack, from structured driving behaviors to domain-specific maneuvers for autonomous GSE operations.
Set the direction for where learned components fit in the planner.
Set technical direction at interfaces between your area and the rest of the stack, and partner with other senior engineers to maintain end-to-end coherence.
Own the functional and software architecture of the autonomy stack, collaborating with neighboring teams for implementation.
Requirements
15+ years of hands-on experience building production autonomy systems, with strong technical depth across localization, perception, prediction, planning, and controls.
Demonstrated track record of shipping autonomy components in production on real vehicles at scale.
Prior experience as the most senior individual contributor in an autonomy organization, setting direction, mentoring, and partnering with engineering leadership.
Deepest technical depth in perception, prediction, or planning (ideally more than one).
Strong software engineering fundamentals in C++ and Python.
Experience with modern deep learning for autonomy, including training, evaluation, deployment, and lifecycle management.
Experience with ROS / ROS 2 and distributed-systems realities of on-vehicle compute.
A bias for execution. Ship, close out problems, and convert ambiguity into running code on a vehicle.
Preferred
Experience with safety-critical or functional-safety-relevant systems.
Experience operating in an Operational Design Domain involving heavy human interaction, mixed traffic, or unstructured environments.
Familiarity with simulation-driven verification and using simulation in a CI/CD pipeline for autonomy.
Benefits
This role offers a compensation range of $300K - $350K.