VIO Front-End Computer Vision Engineer

Harmattan AI

Paris

Sur place

EUR 60 000 - 90 000

Plein temps

14 jours+
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Résumé du poste

Harmattan AI is seeking a Computer Vision Engineer to contribute to the development of the front-end of our visual inertial odometry (VIO) stack. You will work on frame/ stereo matching, camera calibration, and obstruction detection for embedded platforms.

Collaborating with system and optical engineers, you will implement and optimize algorithms, validate them in simulation and real-world environments, and help monitor performance to ensure operational excellence at scale.

Qualifications

  • Master’s degree in Robotics, Physics, or CS required.
  • PhD is a plus.
  • Strong math foundations and Python/C++ skills.
  • Hands-on VIO project experience on industrial products.
  • Passion for computer vision and robotics.
  • Strong communication and teamwork.
  • 100% dedication to Harmattan’s mission and growth.

Responsabilités

  • VIO front-end algorithm development: matching between frames and stereo pairs.
  • Calibration of cameras intrinsic and extrinsic parameters.
  • Detection of obstruction.
  • Implementation and optimization of the algorithmic stack for embedded platforms.
  • Testing, validation and monitoring: simulate and real-world environments; development of inspection tools.
  • Cross-team collaboration with system, optical, and software engineers.

Connaissances

VIO experience
Python
C++
Teamwork
CV passion

Formation

Master's degree in Robotics/Physics/CS
PhD is a plus

Outils

Python
C++

Description du poste

Harmattan AI is seeking a Computer Vision Engineer to contribute to the development of the front-end of our visual inertial odometry (VIO) stack. You will work on frame/ stereo matching, camera calibration, and obstruction detection for embedded platforms.

Collaborating with system and optical engineers, you will implement and optimize algorithms, validate them in simulation and real-world environments, and help monitor performance to ensure operational excellence at scale.

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