Senior Software Engineer, Behavior Planning

AeroVect is transforming ground handling through autonomous driving and robotics-as-a-service solutions for airlines and ground service providers. The company is seeking a Senior Software Engineer to design and implement behavior planning systems for autonomous vehicles operating in complex, low-speed airport environments, including developing algorithms, testing systems, and improving performance.

Responsibilities:

• Develop and implement advanced behavior planning algorithms for autonomous vehicles
• Collaborate with cross-functional teams to ensure robust integration and functionality of planning systems
• Design, write, and maintain efficient and scalable code in C++ and Python
• Contribute to the architecture and continuous improvement of behavior planning software
• Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms
• Analyze system performance and implement enhancements based on data and feedback
• Maintain comprehensive documentation of code, algorithms, and system designs
• Work closely with other engineering teams to ensure seamless coordination and development

Requirements:

• Proficient in modern C++ (11/14/17) and object-oriented programming
• Skilled in Python for rapid prototyping and testing
• Strong in debugging, profiling, and optimizing code
• Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning
• Familiarity with path planning algorithms like A\•, RRT, or optimization-based methods
• Master's degree in Computer Science, Robotics, or a related field
• Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field
• Knowledge of state machines, behavior trees, and decision-making under uncertainty
• Expertise in path planning algorithms such as A\•, D\•, and Rapidly-exploring Random Trees (RRT)
• Knowledge of machine learning techniques, especially in the context of behavior prediction and planning
• Experience with ROS / ROS2
• Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment
• Ensuring that behavior planning algorithms can execute with minimal latency for real-time navigation
• Proficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertainty
• Master's degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus