SLAM Engineer

Location CA-ON-Mississauga
Job ID


The ideal candidate should have substantial experience designing navigation systems for autonomous platforms operating in indoor environments. This includes expertise in object detection, simultaneous localization and mapping, path planning, and low-level controller design. They should take ownership of their work, be self-motivated & practical in their problem-solving and thrive in a fast-paced, highly-collaborative applied research environment.


  • Implementing graph-based SLAM combining laser and vision based sensing in a challenging environment
  • Designing and testing algorithms for long-term deployment (many months without failures)
  • Integrating SLAM solution with larger robotics navigation system
  • Understanding of the effects that SLAM design decisions have on the larger robotic system, including mechanical and electrical designs.
  • Take initiative and lead the systematic evaluation for proposed algorithms.
  • Collaborate with software engineers to optimize algorithms for real-time applications that are power and compute friendly.


  • Masters/PhD in Robotics related field; alternatively, a comparable industry career, with significant experience in delivering holistic robotics solutions
  • At least 2 years developing algorithms for graph-based SLAM, pose estimation, probabilistic filtering, and sensor fusion
  • Experience working with graph optimization backends for a SLAM solution (GTSAM, g2o, CERES)
  • Knowledge of current bleeding edge research, its potential applications to commercial solutions and the ability to fully comprehend relevant new publications.
  • Experience manipulating data from (and modelling errors for) different sensors for robotics platforms, including monocular cameras, stereo cameras, structured light sensors, low-and high-quality LIDAR.
  • Experienced object-oriented programmer using C++ and Python.
  • Experience with commonly used packages such as OpenCV, PCL, ROS, Gazebo
  • Understanding of source control such as GIT
  • Able to take initiative on issues and report results instead of waiting for task lists


  • Bonus: experience writing code for long-term deployments, with final product running for months at a time
  • Bonus: knowledge in GPU programming, GPGPU programming, Linux architecture and GPGPU acceleration
  • Bonus: publications in top robotics conferences (ICRA, IROS, etc.)

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