Autonomous Mapping & Localization Specialist

Blue Signal; Vancouver; Hybrid; CAD 60,000 - 80,000; Full time

Job summary

A robotics company in Vancouver is seeking an Autonomous Mapping & Localization Specialist to develop SLAM algorithms and enhance navigation technologies. Candidates should have relevant degrees and experience with C++, Python, and sensor integration. This role offers competitive compensation, a flexible hybrid work model, and the chance to work on cutting-edge robotics projects.

Benefits

Competitive compensation

Flexible hybrid work model

Access to advanced sensor suites

Qualifications

• Minimum of 2 years of experience working with SLAM algorithms in research or production environments.
• Strong understanding of sensor fusion, state estimation, and probabilistic robotics principles.
• Experience with simulation tools.

Responsibilities

• Develop and optimize SLAM algorithms for robotic applications.
• Design and implement map-building and localization modules.
• Integrate data from diverse sensors to enhance accuracy.

Skills

C++

Python

SLAM algorithms

Sensor fusion

ROS/ROS2

Education

Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or a related field

Tools

ORB-SLAM

Cartographer

RTAB-Map

GTSAM

Gazebo

Isaac Sim

Job description

Overview

Position Title : Autonomous Mapping & Localization Specialist

Location : Vancouver, CA (On-site or Hybrid)

Join a pioneering team at the forefront of autonomous systems development. We are seeking a talented individual to design and implement advanced mapping and localization algorithms that empower mobile robotic platforms to navigate complex environments in real time. This role offers the opportunity to contribute to cutting-edge projects in robotics, computer vision, and sensor fusion, driving innovation in autonomous navigation technologies.

Responsibilities

• Develop and optimize SLAM algorithms (visual, LiDAR, or visual-inertial) tailored for both indoor and outdoor robotic applications.
• Design and implement robust map-building and localization modules to facilitate real-time navigation and autonomy.
• Integrate data from diverse sensors (e.g., LiDAR, stereo / depth cameras, IMUs) to enhance system accuracy and reliability.
• Optimize SLAM systems for performance on embedded or resource-constrained hardware platforms.
• Validate algorithm performance through simulation and real-world testing on robotic platforms.
• Collaborate with cross-functional teams to integrate SLAM outputs with planning and control modules within ROS / ROS2-based architectures.

Qualifications

• Bachelor’s or Master’s degree in Robotics, Computer Science, Electrical Engineering, or a related field.
• Minimum of 2 years of experience working with SLAM algorithms in research or production environments.
• Proficiency in C++ and Python, with hands-on experience using SLAM libraries such as ORB-SLAM, Cartographer, RTAB-Map, or GTSAM.
• Strong understanding of sensor fusion, state estimation, and probabilistic robotics principles.
• Experience with ROS / ROS2 and simulation tools like Gazebo or Isaac Sim.

Preferred Qualifications

• Familiarity with both feature-based and direct SLAM methods.
• Background in visual-inertial odometry and loop closure techniques.
• Experience deploying SLAM systems on embedded hardware platforms (e.g., Jetson, RealSense, Ouster).
• Contributions to open-source SLAM frameworks or relevant robotics research publications.

What We Offer

• Competitive compensation and a flexible hybrid work model based in Burnaby, BC.
• Opportunity to work on foundational technologies in the field of autonomous systems.
• Access to advanced sensor suites and robotic testbeds for hands-on development and testing.
• A collaborative, research-driven environment that encourages technical innovation and professional growth.