Computer Vision Engineer: VIO/SLAM for Mobility (Hybrid/Remote)

Xsens Technologies B.V.; United States; Hybrid; USD 84,000 - 123,000; Full time

Benefits offered by this job

28 paid vacation days

Tax perks for sports memberships and/;

Flexible working hours

Paid volunteer time

Financial planner access

Social events & activities

Job summary

Xsens Technologies B.V. is seeking a hands-on Computer Vision Engineer to expand positioning and localization by fusing visual and inertial data.

You will research, prototype, and deploy VIO/SLAM algorithms, integrating IMU data with monocular or stereo cameras, and collaborate across hardware, firmware and software teams in a modern, international environment. The role focuses on visual-inertial perception, 6-DoF pose estimation, and real-time performance, with a flexible option for hybrid or

Qualifications

• MSc or PhD with hands-on system-building experience.
• Solid understanding of multi-view geometry and camera models.
• Hands-on experience with VO or SLAM systems and open source frameworks.
• Proficiency in Python and/or C++.
• Strong background in linear algebra and state estimation.

Responsibilities

• Design and implement VIO/SLAM pipelines combining inertial and visual data.
• Develop and maintain camera models and calibration routines.
• Optimize algorithms for real-time 6-DoF pose estimation.
• Stay current with CV/robotics research and assess new techniques.
• Collaborate with hardware, firmware, and software teams to deliver end-to-end perception solutions.

Skills

Python / C++

VO/SLAM

Multi-view geometry

Linear algebra

Camera calibration

Education

MSc in CS/EE/Robotics

PhD with hands-on builds

Tools

ROS

OpenCV

Job description

Xsens Technologies B.V. is seeking a hands-on Computer Vision Engineer to expand positioning and localization by fusing visual and inertial data.

You will research, prototype, and deploy VIO/SLAM algorithms, integrating IMU data with monocular or stereo cameras, and collaborate across hardware, firmware and software teams in a modern, international environment. The role focuses on visual-inertial perception, 6-DoF pose estimation, and real-time performance, with a flexible option for hybrid or