15 days ago
Remote, United Kingdom +8 moreSenior
Responsibilities
- Develop and implement advanced behavior planning algorithms for autonomous vehicles.
- Design, write, maintain, and optimize scalable C++ and Python code.
- Contribute to the architecture and continuous improvement of behavior planning software.
- Test and validate planning algorithms in simulated and real-world scenarios.
- Analyze system performance and implement improvements based on data and feedback.
- Collaborate with autonomy and other engineering teams on robust system integration.
- Maintain documentation for code, algorithms, and system designs.
Requirements
- Proficiency in modern C++ 11/14/17 and object-oriented programming.
- Skill with Python for rapid prototyping and testing.
- Strong debugging, profiling, and code optimization abilities.
- Deep understanding of behavior planning algorithms, including state machines, behavior trees, and probabilistic planning.
- Familiarity with path planning algorithms such as A*, RRT, or optimization-based methods.
- 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.
- Preferred: knowledge of decision-making under uncertainty, D*, ROS/ROS2, machine learning for behavior prediction and planning, high-frequency replanning, real-time navigation, optimization techniques, and probabilistic models.
- Preferred: master’s degree or PhD focused on planning, optimization, or control theory.
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.