Automotive Application Engineer

Role overview

A hands-on application engineering role focused on validating and adapting a full-stack edge-AI platform (accelerator silicon and its software toolchain) against automotive market requirements. The position turns customer and market needs into testable criteria, benchmarks the stack against real automotive workloads, and contributes to safety-qualified software as well as collaborative R&D programs and consortia.

Responsibilities

- Translate market and customer requirements into testable evaluation criteria and maintain a current requirements-versus-capability view across releases, with internal evaluation reports for automotive, product, and R&D stakeholders. - Define and run benchmarks around real automotive use cases such as ADAS perception, surround view/parking, BEV/occupancy, DMS/OMS, and sensor fusion; port, quantize, and optimize workloads while tracking regressions. - Identify and close gaps between the current stack and automotive expectations across the toolchain, runtime, OS/middleware integration, determinism, and diagnostics, and prototype runtime integration into automotive environments. - Contribute hands-on to the ASIL-B/ASIL-D software stack (safety runtime, diagnostics, monitoring) and assess integration effort for Tier-1/OEM scenarios, feeding gaps back as prioritized findings. - Own or co-own technical work packages in collaborative R&D projects and automotive/edge-AI consortia, coordinating with OEM, Tier-1, and research partners while keeping the work aligned with the internal roadmap. - Track automotive AI/ADAS trends and competitive benchmarks, translating findings into prioritized recommendations for product and engineering.

Requirements

- 4–8 years in embedded software or application engineering within automotive or automotive semiconductors, with strong embedded C and Python for tooling and test automation. - Real-time systems and safety-qualified development in an ASIL-B/ASIL-D context, including ISO 26262 requirements, safety mechanisms, diagnostics, and supporting evidence. - Embedded development on constrained targets (board bring-up, drivers, BSPs) using standard automotive toolchains on embedded Linux, with exposure to QNX or AUTOSAR. - Validation on target hardware, including bench/HIL testing and characterization across the automotive temperature range. - Structured requirements-to-evidence mindset and clear technical writing. - Fluent English; approximately 15% travel for consortium meetings and partner labs.

Nice to have

- Exposure to deep-learning frameworks (PyTorch, ONNX), model deployment on embedded targets, and quantization or graph compilation concepts. - Familiarity with computer-vision and camera-based automotive perception workloads. - Experience in collaborative R&D projects at the European or national program level. - Deeper experience with AUTOSAR Adaptive, Android Automotive OS, SOME/IP, DDS, or sensor interfaces such as MIPI CSI-2 and GMSL/FPD-Link. - Awareness of ISO 21434 and A-SPICE, with exposure to vehicle E/E architectures. - An additional European language.

Benefits and work setup

- Flexible working arrangements: office-based across several European countries (Belgium, the Netherlands, Switzerland, Italy, UK), fully remote from any European country, or relocation support to Italy or the Netherlands. - Priority consideration given to candidates based in or interested in being based in Belgium or Italy. - Compensation package including a pension plan, extensive employee insurances, and the option to obtain company shares. - Open, international culture with collaborative ownership and freedom with responsibility, committed to equal opportunity and a diverse, inclusive workplace.