Senior Software Engineer, Behavior Planning

🕒 il y a 19 jours

🇨🇦 Canada – Télétravail

💵 CA$160 000 - CA$200 000 / an

⏰ Temps Plein

🟠 Senior

🧑‍💻 Développeur Full-Stack

👻 Score fantôme 21%

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🗣️🇺🇸🇬🇧 Anglais requis

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AeroVect

11 - 50 employés

📦 Logistique

💼 Conseil

🚀 Aérospatiale

💰 Seed Round en 2022-07

Logistics • Consulting • Aerospace

AeroVect est une entreprise technologique spécialisée dans l'automatisation avancée des équipements de soutien au sol (GSE) dans l'industrie de l'aviation. Le produit phare de la société, AeroVect Driver, est un système de conduite autonome hautement évolutif, compatible avec tous les fabricants, conçu pour améliorer la sécurité, la productivité et la durabilité des opérations de manutention au sol. Plébiscitée par les grandes compagnies aériennes et les prestataires de services au sol, AeroVect vise à révolutionner les opérations côté piste avec sa technologie de conduite autonome de premier plan, développée dans la Silicon Valley pour le marché mondial de l'aviation.

Description

• 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 • Own the design and implementation of key modules in the behavior planner • Work closely with the autonomy engineering team and report to the Planning Tech Lead

🎯 Exigences

• 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 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

🏖️ Avantages

• Equity

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