Senior Software Engineer, Motion Planning - Amsterdam - AeroVect

    AeroVect
    AeroVect Amsterdam

    1 dag geleden

    Beschrijving
    Senior Software Engineer, Motion Planning

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    AeroVect Amsterdam, North Holland, Netherlands

    Who We Are

    AeroVect 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 will

    • 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
    You have
    • Proficient in modern C++ (11/14/17) and object‑oriented programming
    • Skilled in Python for rapid prototyping and testing
    • Strong debugging, profiling, and optimization skills
    • 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
    We prefer
    • 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 xhsqlod and planning
    • Experience with ROS / ROS2
    • Implemented systems capable of re‑planning 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 (plus)
    Seniority level

    Mid‑Senior level

    Employment type

    Full‑time

    Job function

    Information Technology

    Industries

    Airlines and Aviation


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