We’re Hiring for 2024!

Open Team Positions

All team members are expected to contribute on average 10 hours of work per week, counted with participation in weekly work sessions during a weekday evening and Saturday work sessions at UTIAS campus (10am-4pm). Applications will be reviewed on a rolling basis and only successful applicants will be contacted via email.

Please refer to the following job descriptions for sub-teams that are still actively hiring!

  • As a GUI general member, you will be developing our Human-Machine Interface, helping us design intuitive user controls for our autonomous vehicle, and visualizing key information about what our vehicle sees and what it plans to do.

    Desired Qualifications:

    - Experience with Python or C++

    - Working understanding of ROS/2 concepts

    - Working understanding of RVIZ

    - UI design experience, PyQT preferred

  • As a Localization general member, you will be working on developing algorithms to improve the accuracy of our vehicle's state estimation, by performing multi-sensor fusion online, and creating offline calibration and offset analysis tools.

    Desired Qualifications:

    - Experience with Python, C++ preferred

    - Working understanding of ROS/2 concepts

    - Good Understanding of Kalman Filters

  • As a 3D Object Detection general member, you will be helping develop our perception stack by deploying algorithms to find objects within our LiDAR point clouds, allowing our vehicle to see the world around it.

    Desired Qualifications:

    - Experience with Python or C++

    - Working understanding of ROS/2 concepts

    - Experience with PointCloudLibrary or Open3D

    - Deep Learning Experience is a bonus!

  • As an Electrical general member, you will be working with CAD software to design and simulate PCBs. You will also assist with the assembly, validation, and testing of electrical components, which allow our vehicle computer to interface with sensor.

    Desired Qualifications:

    - Experience with Python or C++

    - Experience working with PCB design software (Altium/Eagle)

    - Experience with soldering

    - Knowledge of basic electronics, circuits, and electrical components

  • As a Mechanical lead, you will be working at the Garage every Saturday in person (non-negotiable). You will be helping to lead the mechanical team in designing sensor suite platforms from conceptualization to final manufacture. Strong design skills, CAD experience, and ability to manage teams efficiently is greatly desired.

    Desired Qualifications:

    - Experience with CAD

    - Experience with FEA Analysis

    - Rapid prototyping using 3D Printing/Laser Cutting

    - Hands-on building skills

Why Join Us?

  1. World-class Mentorship: work alongside our industry partners such as GM, Intel, Cepton, and Novatel directly

  2. Invaluable Practical Experience: not every student got a chance to develop an algorithm onto a vehicle and test it out

  3. Incredible Resources: our own car, compute servers, state-of-the-art sensors, dedicated lab space

  4. Course Credits: students who join our team have the option to pursue an undergraduate thesis or capstone project with us, supervised by Professors Steve Waslander, Jonathan Kelly, Tim Barfoot, and Angela Schoellig.

  5. A Winning Team: We have established ourselves as a premier university self-driving car team. You will have an opportunity to build on this legacy.

Different together

aUToronto is committed to creating a diverse environment and is proud to be an equal opportunity team. All qualified applicants will receive consideration without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, or age.

aUToronto is also committed to educating young and committed 1st-year and 2nd-year students with the latest and greatest robotics technology. For 1st-year and 2nd-year students, we are more interested in your commitment to learning and being the best autonomous vehicle engineer than your technical understanding of a given topic.