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Open nowPosted 7 days ago

Senior Software Engineer, Behavior Planning

AeroVect43 open roles

Pay
CA$160,000 – CA$200,000 a year
Where
Toronto - Remote
Work mode
Remote
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Your applicationOpen nowSenior Software Engineer, Behavior PlanningAeroVect · Toronto - Remote

  1. YouYes, apply to this one.

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The clock on this job

Early applications get read.

12.9% of postings close within 7 days. Measured by our own scanner across the market. AeroVect postings stay open a median of 37 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 12.9%7 days
  4. 21.0%14 days
  5. 35.6%30 days
  6. 58.5%60 days
This job: posted 7 days ago

AeroVect median: 37 days open

The posting

WHO WE ARE

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com http://www.aerovect.com.

We are looking for an experienced Senior Software Engineer who can design and build best-in-class behavior planning systems for autonomous driving in structured, low-speed environments.

In this role, you'll own the design and implementation of key modules in the behavior planner — the decision-making layer that determines what the vehicle should do in complex, dynamic airside scenarios. You'll work at the intersection of mission-level goals and motion-level execution, tackling problems in multi-agent interaction modeling, rule-based and learned decision-making, and robust handling of edge cases unique to airport ground operations.

This opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team.

YOU WILL

- 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

YOU HAVE

- 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

WE PREFER

- 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

- Implementing systems that can re-plan at high frequencies to adapt to dynamic changes in the environment

- Ensuring that 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

- Master’s degree or PhD in Robotics, AI, Mathematics, or a related field with a focus on planning, optimization, or control theory is a plus

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