15 days ago
Remote, CanadaSenior
Responsibilities
- Develop and implement behavior-planning algorithms for autonomous vehicles.
- Design, write, maintain, and optimize scalable C++ and Python software.
- Contribute to the architecture and continuous improvement of behavior-planning systems.
- Integrate planning systems with cross-functional autonomy and engineering teams.
- Test and validate planning algorithms in simulated and real-world scenarios.
- Analyze system performance and implement improvements for dynamic, real-time navigation.
- Document code, algorithms, and system designs.
Requirements
- Master’s degree in Computer Science, Robotics, or a related field.
- At least 3 years of industry experience in autonomous driving, robotics, or a related field.
- Proficiency in modern C++ and object-oriented programming.
- Proficiency in Python for prototyping and testing.
- Strong debugging, profiling, and code-optimization skills.
- Deep understanding of behavior-planning algorithms, including state machines, behavior trees, and probabilistic planning.
- Familiarity with path-planning algorithms such as A*, RRT, and optimization-based methods.
- Preferred qualifications include ROS/ROS2 experience, machine learning knowledge, high-frequency replanning, real-time low-latency navigation, optimization techniques, and probabilistic modeling.
- A master’s degree or PhD in Robotics, AI, Mathematics, or a related field focused on planning, optimization, or control theory is preferred.
About AeroVect
AeroVect builds autonomous driving systems and software to automate airport ground service equipment, improving ramp logistics for airlines, airports, and ground handling providers. It deploys and supports autonomy for fleets used by major carriers and ground service companies. Founded in 2020 and headquartered in South San Francisco, it is a privately held Series A company.