Embedded Software Engineer

Roles & Responsibilities:

• Develop and implement algorithms for comprehensively processing radar data and testing strategies, including unit testing, integration testing, and system-level testing, to ensure the reliability and robustness of the Digital Signal Processing Chain.

• Collect and catalog field data, ensuring that it is organized and easily accessible for thorough analysis and processing. Systematically organize and analyze research data to prepare it for integration into a Machine Learning model.

• Implement machine learning and statistical techniques to improve the classification accuracy of on-road objects.

• Extract important insights from radar data. Incorporate data processing algorithms into radar systems, and enhance algorithms for detecting, tracking, and classifying targets.

• Design and develop software tools for radar data analysis and visualization.

• Collaborate with cross-functional teams such as hardware engineers, software developers, and quality assurance engineers to facilitate the smooth integration of firmware with hardware and software ensuring system compatibility.

• Conduct testing and validation of data processing techniques. Troubleshoot and debug, identify and resolve firmware-related issues, conduct root cause analysis, and implement corrective actions to deliver robust solutions.

• Stay updated with the latest advancements in radar data processing technologies.

• Prepare technical documentation, including algorithm descriptions, test plans, and reports.

• Create and maintain thorough technical documentation, including test plans and user manuals, to support effective collaboration and ensure knowledge transfer among team members.

• Experience with vehicle CAN network systems & diagnostics are preferred.

• Attend Software reviews

Required Skills & Qualifications:

• Core Embedded Skills: Proficiency in Embedded C and experience with flow-charts for algorithm logic design.

• Digital Signal Processing (DSP): Solid understanding of DSP fundamentals, including Fast Fourier Transform (FFT), windowing techniques, and signal conditioning.

• Filter Design: Knowledge of designing and implementing Digital Filters (FIR/IIR) to enhance signal quality and noise reduction.

• Tracking & Estimation: Understanding of object tracking algorithms and state estimation techniques, specifically Kalman Filters (Linear or Extended) for target trajectory prediction.

• Bachelor or Master Degree in Engineering. Specialised in Electronics, Mechatronics or Telecommunications.

• Understanding of advanced driver assistance sensors such as RADAR primarily, added advantage on understanding of camera, ultrasonic and LIDAR.

• Experience with automotive environmental, reliability, and safety requirements.

• Excellent team-working, organisation, communication & networking skills.

• Fluent English (verbally and in writing) and good documentation skills.

Ways to stand out from the crowd:

• Experience of test and validation of ADAS systems, HIL, SIL & Vehicle is desired, but not essential. (Preferable dSPACE HIL Plant Modeling using Matlab Simulink /Stateflow)

• Familiarity with ISO26262 , but not essential.