2 months ago
Base Salary
$180k - $220k/yr
Responsibilities
- Develop and implement advanced behavior planning algorithms for autonomous vehicles.
- Design, write, maintain, and optimize efficient and scalable C++ and Python software.
- Own key behavior planner modules covering decision-making, multi-agent interaction, rule-based and learned planning, and edge-case handling.
- 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 to integrate planning systems and maintain documentation.
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.
- Skill in 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.
- Preferred qualifications include ROS/ROS2 experience, machine learning knowledge for behavior prediction and planning, high-frequency replanning, real-time navigation, optimization techniques, and probabilistic modeling.
- A master’s degree or PhD 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.