Senior Software Engineer, Behavior Planning

🕒 September 17

🌐 United Kingdom, Italy, +6 more countries – Remote

🇬🇧 United Kingdom – Remote 🇮🇹 Italy – Remote 🇵🇱 Poland – Remote 🇸🇪 Sweden – Remote 🇩🇪 Germany – Remote 🇳🇱 Netherlands – Remote 🇫🇷 France – Remote 🇮🇪 Ireland – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 30%

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AeroVect

WebsiteLinkedInAll Job Openings

11 - 50 employees

📦 Logistics

💼 Consulting

🚀 Aerospace

💰 Seed Round on 2022-07

Logistics • Consulting • Aerospace

AeroVect is a technology company that specializes in advanced automation for Ground Support Equipment (GSE) in the aviation industry. The company's flagship product, AeroVect Driver, is a highly scalable, OEM agnostic self-driving system designed to improve safety, productivity, and sustainability in ground handling operations. Trusted by leading airlines and handlers, AeroVect aims to revolutionize airside operations with its premier self-driving technology, built in Silicon Valley for the global aviation market.

📋 Description

• Design and build behavior planning systems for autonomous driving in structured, low-speed environments • Own the design and implementation of key behavior-planner modules that determine vehicle actions in complex, dynamic airside scenarios • Address multi-agent interaction modeling, rule-based and learned decision-making, and airport ground-operation edge cases • Develop and implement advanced behavior planning algorithms for autonomous vehicles • Collaborate with cross-functional teams to integrate planning systems robustly • Design, write, and maintain efficient, scalable C++ and Python code • Contribute to behavior-planning software architecture and continuous improvement • Test algorithms extensively in simulated environments and real-world scenarios • Analyze system performance and implement data- and feedback-driven enhancements • Maintain documentation for code, algorithms, and system designs • Coordinate development with other engineering teams

🎯 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 • 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 • Experience implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment • Experience ensuring 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

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