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.