
Aerospace âą Transport âą Artificial Intelligence
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.
November 19

Aerospace âą Transport âą Artificial Intelligence
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.
âą Develop and implement advanced behavior planning algorithms for autonomous vehicles âą Collaborate with cross-functional teams to ensure robust integration and functionality of planning systems âą Design, write, and maintain efficient and scalable code in C++ and Python âą Contribute to the architecture and continuous improvement of behavior planning software âą Conduct extensive testing in simulated environments and real-world scenarios to validate and refine behavior planning algorithms âą Analyze system performance and implement enhancements based on data and feedback âą Maintain comprehensive documentation of code, algorithms, and system designs âą Work closely with other engineering teams to ensure seamless coordination and development
âą Proficient in modern C++ (11/14/17) and object-oriented programming âą Skilled in Python for rapid prototyping and testing âą Strong in debugging, profiling, and optimizing code âą Deep understanding of behavior planning algorithms such as state machines, behavior trees, and probabilistic planning âą Familiarity with path planning algorithms like A*, RRT, or optimization-based methods âą Masterâs degree in Computer Science, Robotics, or a related field âą Minimum of 3 years of industry experience in autonomous driving, robotics, or a related field
âą Health insurance âą Paid time off âą Flexible work arrangements âą Professional development
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