Visual-Inertial SLAM Engineer (Hybrid/Remote)

Xsens Technologies B.V.; Enschede; Hybrid; EUR 70,000 - 110,000; Full time

Benefits offered by this job

28 paid vacation days

Tax perks for sports/bike

Flexible working hours

Volunteer time with Stichting Present

Financial planner access

Social events

Job summary

Xsens Technologies B.V. is seeking a hands-on Computer Vision Engineer to advance visual-inertial localization at our Enschede site, with hybrid/remote options.

You will research, prototype, and deploy VIO/SLAM solutions, integrating IMU data with camera inputs, and collaborate across hardware, firmware, and software teams. The ideal candidate has a strong background in computer vision and robotics, with 3+ years of industry or research experience, and proficiency in Python and C++.

Qualifications

• MSc in CS/EE/Robotics or PhD with hands-on system-building.
• Strong multi-view geometry, camera models and physics.
• Hands-on VO or SLAM with open-source frameworks.
• Proficiency in Python and C++.
• Strong math: linear algebra, probability, state estimation.
• Prefer: automotive/robotics industry experience.
• Prefer: IMU signal processing knowledge.
• Prefer: GPU-accelerated computing and real-time optimization.
• Prefer: ROS and OpenCV experience.

Responsibilities

• Design and implement state-of-the-art VIO and SLAM pipelines.
• Develop and maintain camera models, calibration routines, and sensor synchronization.
• Apply optimization and filtering to robust 6-DoF pose estimation.
• Stay current with CV research and assess feasibility of new techniques.
• Collaborate with hardware, firmware, and software teams to deliver perception solutions.

Skills

Python / C++

VO/SLAM

Multi-view geometry

Linear algebra / probability / state估

OpenCV familiarity

Education

MSc in CS / EE / Robotics

PhD with hands-on system-building

Tools

ROS

OpenCV

Job description

Xsens Technologies B.V. is seeking a hands-on Computer Vision Engineer to advance visual-inertial localization at our Enschede site, with hybrid/remote options.

You will research, prototype, and deploy VIO/SLAM solutions, integrating IMU data with camera inputs, and collaborate across hardware, firmware, and software teams. The ideal candidate has a strong background in computer vision and robotics, with 3+ years of industry or research experience, and proficiency in Python and C++.