We are looking for a Software Engineer to join our ADAS System project. The goal of this role is to design, implement, and optimize algorithms and applications that detect environmental interference. You will be working on a diverse stack involving signal processing, computer vision, and machine learning, targeting both general-purpose processors and embedded platforms.
Responsibilities:
- Design and develop the application skeleton for the ADAS Systems module
- Implement signal processing algorithms in the frequency domain
- Develop motion detection and entropy-based analysis algorithms
- Design lightweight edge detection algorithms tailored for resource-constrained environments
- Prepare and integrate machine learning models for blockage detection
- Develop a complete blockage detection algorithm combining classical and ML-based approaches
- Re-implement existing C++ signal processing algorithms for dedicated signal processor architectures
- Optimize and compress ML models for deployment on embedded NPUs
- Conduct Software-in-the-Loop (SIL) validation to ensure functional correctness and performance Collaborate with cross-functional team
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Requirements:
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field
- Experience in automotive or ADAS-related projects
- Experience in C++ v20
- Experience working with automotive ECUs and embedded software integration.
- Strong background in digital signal processing and computer vision
- Experience with frequency domain transformations
- Knowledge of motion detection and entropy analysis techniques
- Familiarity with CAN
- Experience with embedded deployment and optimization of ML models
- Understanding of NPU hardware and ML inference on constrained devices
- Familiarity with Software-in-the-Loop (SIL) testing environments
Apply now or reach out to us directly to learn more.
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