Autonomy Engineer II

About the role

You will architect and implement core autonomy stacks that allow our eVTOL aircraft to perceive, reason, and act in complex three-dimensional airspace. This role owns the development of advanced navigation, planning, and decision-making systems critical for safe autonomous flight operations. You will design and validate perception algorithms that process heterogeneous sensor data to build a reliable environmental model for our aircraft. You will collaborate closely with cross-functional teams to translate high-level mission requirements into robust software components and interfaces. You will ensure that autonomy features meet stringent safety and reliability standards required for both consumer and public service applications. You will contribute to the creation of scalable autonomy frameworks that support our current and future aircraft platforms, including the Helix family. You will analyze flight data to refine autonomy behaviors and improve system performance in real-world conditions. You will mentor junior engineers and contribute to technical documentation and best practices for the autonomy group.

Key facts

What you'll do

Architect and maintain the core autonomy software stack for real-time operation in embedded and cloud environments.

Implement and optimize sensor fusion pipelines that integrate data from cameras, lidar, radar, and inertial measurement units for state estimation.

Develop advanced navigation and path-planning algorithms that account for dynamic obstacles, weather, and regulatory constraints.

Design and simulate decision-making behaviors for mission planning, route optimization, and contingency handling in uncertain environments.

Collaborate with flight test teams to collect data, reproduce issues, and validate autonomy features through rigorous testing.

Partner with hardware engineers to ensure autonomy solutions are aligned with vehicle design constraints and sensor capabilities.

Create modular and reusable software components that enable rapid iteration and integration across different aircraft platforms.

Define and maintain simulation environments that replicate complex operational scenarios to support continuous development.

Lead technical investigations to diagnose and resolve complex autonomy failures observed in simulation or flight testing.

Contribute to the establishment of safety cases and verification procedures that demonstrate compliance with industry standards.

Mentor engineers at various levels by providing code reviews, technical guidance, and constructive feedback during project execution.

Translate evolving product requirements into technical specifications that guide the development of autonomy features.

Support the deployment of autonomy updates through robust release processes that prioritize safety and reliability.

Engage with the broader autonomy community by reviewing literature, tools, and methodologies relevant to aerial robotics.

Requirements

Candidates must have a Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or a related technical field.

You must have demonstrated experience with programming in C++ and Python for real-time or robotic systems.

You should possess a strong understanding of control theory, estimation, and probabilistic methods used in robotics.

You must have hands-on experience with sensors such as cameras, lidar, and inertial measurement units and their calibration.

You should have a proven track record of developing navigation or planning algorithms for dynamic environments.

You must have experience working in safety-critical domains and understand functional safety concepts relevant to aviation.

You should be comfortable working with simulation tools and data pipelines used for testing autonomous systems.

You must have excellent problem-solving skills and the ability to debug complex systems under tight deadlines.

Nice to have

Experience with air mobility platforms or eVTOL vehicles is highly valued.

Knowledge of aviation regulations and standards such as DO-178C or DO-331 is a significant advantage.

Familiarity with machine learning frameworks for perception or prediction tasks is preferred.

Experience with formal methods or safety analysis for autonomous systems is appreciated.

Background in public safety or defense applications is considered a plus.

Practical notes

This role may require occasional travel to test sites or partner facilities as needed for project milestones.

Employment is contingent upon successful completion of background checks and relevant security screenings.

Candidates must be eligible to work in the United States without sponsorship for this position.

The position is based in either Palo Alto, California, or Miami, Florida, with flexibility for remote collaboration within approved guidelines.