Executive snapshot
- Experience: ca. 2 Jahre
- Seniority: Senior
- Work mode: Verhandelbar
- Availability: Sofort verfügbar
- Region: Deutschland / EU
- Focus: Automotive, Robotics, Embedded Systems, Industrial Electronics
At a glance
Profile ID
DP-207770
Role
Robotics Software Development, Embedded Systems, Sensor Integration, ADAS Development
Seniority
Senior
Experience
ca. 2 Jahre
Work mode
Verhandelbar
Availability
Sofort verfügbar
Region
Deutschland / EU
Languages
German: C1, English: C1
Engagement models
Festanstellung, Projektarbeit
Indicative rate
Nach Absprache
Short profile
Experienced Robotics Software Developer specializing in ROS, Automotive LiDAR, and Radar. Possesses practical experience in software and sensor integration on ADAS prototype vehicles as well as in deep learning-based radar perception. Expertise in C++, Python, and Embedded Systems, complemented by an M.Sc. in AI and Autonomous Driving. Reliable in diagnosing and resolving hardware-software errors and implementing complex communication systems.
Focus (domains)
AutomotiveRoboticsEmbedded SystemsIndustrial ElectronicsIndustrialSoftwareEmbeddedTestingManagement
Core skills
ROSC++PythonDeep LearningSensor IntegrationTeleoperationHardware-Software InterfaceFault DiagnosisSystem IntegrationPoint Cloud ProcessingEmbeddedHardwareSoftwareMATLABTestingValidationE-Mobility / Automotive / Industrial ElectronicsEmbedded Systems
Tools & technologies
ROSNVIDIA JetsonGStreamerMATLABPythonC++SolidWorksGitCEmbeddedHardwareSoftwareTestingValidation
Track record & project highlights
Development and maintenance of ROS-based software on NVIDIA Jetson platform for an ADAS prototype vehicle, including implementation of a 4G/5G teleoperation solution and live video pipeline (GStreamer). Diagnosis and resolution of hardware-software errors in actuators and control signals to ensure prototype demonstration capability. Research and implementation of lossless compression methods for LiDAR sensor data (point clouds) and investigation of preprocessing techniques. Development of deep learning models for radar perception, including object detection and tracking for automotive applications.
