Senior Software Engineer, Behavior Planning

AeroVect

. Develop and implement advanced behavior planning algorithms for autonomous vehicles .

Posted 10/23/2026full-timeRemote • CanadaSenior💰 CA$160,000 - CA$200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing advanced behavior planning algorithms for autonomous vehicles, with proficiency in C++ and Python. Capable of optimizing code for real-time navigation and collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Modern C++ ProficiencyBehavior Planning AlgorithmsPython Rapid PrototypingROS / ROS2 ExperienceMachine Learning Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Behavior Planning AlgorithmsModern C++ (11/14/17)Python ProgrammingDebugging and ProfilingOptimization TechniquesPath Planning AlgorithmsProbabilistic ModelsState MachinesBehavior TreesRe-planning Systems

Soft Skills

CollaborationProblem-SolvingDocumentation Skills

Certifications & Qualifications

Master’s Degree in Computer ScienceMaster’s Degree in Robotics

Industry Keywords

Autonomous DrivingRoboticsBehavior PredictionDynamic Environment AdaptationMulti-Agent Interaction Modeling

Tech Stack

Tools & technologies

PythonC++

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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