5 hours ago
Remote, United Kingdom +9 moreSenior
Responsibilities
- Develop and implement advanced behavior planning algorithms for autonomous vehicles.
- Design, write, maintain, and architect efficient and scalable behavior-planning software in C++ and Python.
- Integrate planning systems with cross-functional and autonomy engineering teams.
- Test and validate algorithms in simulated environments and real-world scenarios.
- Analyze system performance and implement improvements based on data and feedback.
- Document code, algorithms, and system designs.
- Support high-frequency replanning and minimal-latency execution for real-time navigation.
Requirements
- Proficiency in modern C++ and object-oriented programming.
- Proficiency in Python for rapid 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 methods such as A*, RRT, or optimization-based approaches.
- 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 qualifications include D*, ROS/ROS2, machine learning for behavior prediction and planning, optimization techniques, probabilistic models, and planning under uncertainty.
- Preferred qualifications include a 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.