VINFAST

Computer Vision / Perception Engineer (Senior/Expert)

Stellenbeschreibung:

Frankfurt am Main, Germany | Posted on 07/10/2026

VinFast is a pioneering electric vehicle (EV) company committed to revolutionizing the automotive industry with sustainable and innovative mobility solutions. As a leading player in the EV market, VinFast is dedicated to delivering high-quality, cutting-edge electric vehicles that redefine the driving experience. Our team consists of passionate professionals driven by a shared vision of creating a greener and more sustainable future through innovation, technology, and excellence.

Join our ADAS/Monitoring System team as a Computer Vision / Perception Engineer. In this role, you will contribute to the development of advanced perception capabilities for smart vehicles. Your work will focus on SLAM and multi-sensor fusion, precise sensor calibration, developing advanced deep learning–based perception models, and end-to-end validation through SIL/HIL and real-vehicle testing.

Key Responsibilities

  • Design, develop, and optimize SLAM and multi-sensor fusion algorithms using data from cameras, IMU, radar, ultrasonic sensors, and other onboard sensors.
  • Develop and maintain sensor calibration pipelines, including camera intrinsics/extrinsic and cross-sensor calibration.
  • Develop, train, and improve advanced deep learning models for perception of motion planning.
  • Integrate perception, fusion, and calibration algorithms into embedded automotive and ADAS platforms.
  • Perform system integration and validation through Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and real-vehicle testing.
  • Analyze test results, identify failure modes, and continuously improve accuracy, robustness, and real-time performance.
  • Collaborate with software, hardware, and vehicle integration teams to deliver production-ready ADAS solutions.

Requirements

  • Diploma or bachelor’s degree in Mechatronics, Robotics, Automation Engineering, Computer Science, or a closely related field.
  • From 7 years hands‑on experience in R&D and/or production projects within automotive, robotics, or autonomous systems.
  • Strong programming skills in C++ and Python.
  • Practical experience with computer vision and linear algebra libraries such as OpenCV and Eigen.
  • Fundamental understanding of sensor‑based systems and real‑world deployment considerations.

Preferred Qualifications

  • Experience or strong knowledge in SLAM, 3D reconstruction, localization, and multi‑sensor fusion algorithms.
  • Hands‑on experience with sensor calibration methods, including camera intrinsics/extrinsic and cross‑sensor calibration.
  • Exposure to deep learning models for perception, including training, optimization, or deployment.
  • Experience with SIL/HIL testing frameworks, simulation environments, and validation of real vehicles.
  • Knowledge of robotics fundamentals, coordinate transformations, vehicle kinematics, and vehicle modeling or simulation.
  • Strong problem‑solving skills and the ability to apply theoretical concepts to practical, production‑level systems.
  • Ability to work effectively both independently and within cross‑functional, collaborative teams.

With respect to all your personal data shared to VinFast in the application and the entire recruitment process of VinFast, by clicking “Apply”, submitting your resumé/CV and/or participating in VinFast's recruitment process, you agree that you have read VinFast's Personal Data Protection Policy ("Policy") posted at or you agree to the Policy and consent for VinFast to process your personal data in accordance with the Policy and the applicable regulations on personal data protection. To all recruitment agencies: VinFast does not accept agency resumes. Please do not forward resumes to our careers alias or other VinFast employees. VinFast is not responsible for any fees related to unsolicited resumes.

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Stelleninformationen

  • Veröffentlichungsdatum:

    30 Jul 2026
  • Standort:

    Frankfurt

    Einsatzort:

    null
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

    Development & IT
  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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