Who We AreAeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.We are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments.In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations.This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team.You WillDevelop and implement advanced behavior planning algorithms for autonomous vehiclesCollaborate with cross-functional teams to ensure robust integration and functionality of planning systemsDesign, write, and maintain efficient and scalable code in C++ and PythonContribute to the architecture and continuous improvement of behavior planning softwareConduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithmsAnalyze system performance and implement enhancements based on data and feedbackMaintain comprehensive documentation of code, algorithms, and system designsWork closely with other engineering teams to ensure seamless coordination and developmentYou HaveProficient in modern C++ (11/14/17) and object-oriented programmingSkilled in Python for rapid prototyping and testingStrong in debugging, profiling, and optimizing codeDeep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planningFamiliarity with path planning algorithms like A*, RRT, or optimization-based methodsMaster’s degree in Computer Science, Robotics, or a related fieldMinimum of 3 years of industry experience in autonomous driving, robotics, or a related fieldWe PreferKnowledge of state machines, behavior trees, and decision-making under uncertaintyExpertise 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 planningExperience with ROS / ROS2Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environmentEnsuring that behavior planning algorithms can execute with minimal latency for real-time navigationProficiency in optimization techniques and probabilistic models for making informed planning decisions under uncertaintyMaster’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plusCompensation$144K - $180K #J-18808-Ljbffr