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# Application Engineer - Vehicle Data Processing

- **Company:** Ivex
- **Location:** Leuven, Belgium
- **Contract:** Permanent contract
- **Skills:** Secure Shell (SSH), Amazon Web Services, Data Structures, Software Debugging, Linux, Python (Programming Language), Linux System Administration, Machine Learning, NumPy, Data Driven Tests, Data Processing, Cloud Platform System, Git, Pandas, Information Technology, NVIDIA Jetson, Lidar, GNSS, Docker
- **Published:** November 12, 2026
- **Apply:** https://ivex.ai/careers/application-engineer-vehicle-data-processing

## About the Role

* Master's degree or higher in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
 * Strong Python proficiency, with hands-on experience using Pandas and NumPy for data processing and analysis.
 * Experience working with vehicle sensor data, including LiDAR point clouds and vehicle camera images.
 * Familiarity with vehicle data structures such as vehicle state, object lists, and lane lines (or closely related representations).
 * Solid working knowledge of Linux, SSH, Git, and Docker for running and troubleshooting analysis environments.
 * Excellent communication skills in English (written and verbal), with the ability to explain technical results clearly.

Nice to have

 * Experience with cloud environments, especially AWS (a strong plus).
 * Practical experience in Machine Learning for data-driven analysis tasks.
 * Experience with embedded platforms like NVIDIA Jetson or similar.
 * Experience with sensor drivers and data acquisition (including images, point clouds, and GNSS data).

## Description

* Execute customer-facing data analyses using IVEX tools and pipelines, turning raw vehicle data into structured results and actionable insights.
 * Process and validate multi-sensor vehicle datasets including LiDAR point clouds, vehicle camera images, GNSS, and related signals.
 * Work with common vehicle data types such as vehicle state, object lists, lane line detections, and derived KPIs.
 * Debug, adapt, and run analysis workflows in Linux environments, often via SSH and containerized setups.
 * Collaborate with customers and internal engineering teams to clarify requirements, troubleshoot issues, and deliver results efficiently.