Senior Software Engineer, Behavior Planning

🔥 13 hours ago

🇨🇦 Canada – Remote

💵 CA$160k - CA$200k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• 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 behavior-planner modules for autonomous driving in structured, low-speed environments • Address multi-agent interaction modeling, rule-based and learned decision-making, and airport-ground-operation edge cases • Work at the intersection of mission-level goals and motion-level execution

🎯 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 • 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 • Ability to ensure behavior planning algorithms execute with minimal latency for real-time navigation • Proficiency in optimization techniques and probabilistic models for planning decisions under uncertainty

🏖️ Benefits

• Equity