Automotive Application Engineer

Axelera AI is seeking a hands-on Automotive Application Engineer to test and adapt its full-stack edge-AI solution against automotive market requirements. The role involves porting and quantizing automotive AI workloads, benchmarking, and contributing to ASIL-B/ASIL-D safety software, working closely with R&D and functional safety teams. Requires 4-8 years in embedded software or application engineering with strong embedded C and Python.

Core AIHybridFull-timeMid LevelEmbedded CPython

Automotive Application Engineer

Axelera AI is seeking a hands-on Automotive Application Engineer to test and adapt its full-stack edge-AI solution against automotive market requirements. The role involves porting and quantizing automotive AI workloads, benchmarking, and contributing to ASIL-B/ASIL-D safety software, working closely with R&D and functional safety teams. Requires 4-8 years in embedded software or application engineering with strong embedded C and Python.

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Core AIHybridFull-timeMid LevelEmbedded C

Salary

Not specified

Work Location

Eindhoven, North Brabant, Netherlands, NL

Work Model

Hybrid; flexible working arrangement with options to work from an office, fully remotely from any European country, or relocate to Italy or the Netherlands

Experience Required

8 years

Employment Type

Full-time

Experience Level

4–8 years in embedded software or application engineering

Core Qualifications

Technical (Must-have)

Embedded CPythonReal-time systemsASIL-B/ASIL-DISO 26262Embedded LinuxQNXAUTOSARBoard bring-upDriversBSPsCross-compilationTrace/debugCIMISRA

Soft Skills

Structured mindsetClear technical writingCollaborationCoordination

Preferred Qualifications

Technical (Nice-to-have)

PyTorchONNXQuantizationGraph compilationComputer visionHorizon EuropeChips JUAUTOSAR AdaptiveAndroid Automotive OSSOME/IPDDSMIPI CSI-2GMSL/FPD-LinkISO 21434A-SPICE

Key Responsibilities

•Translate market and customer requirements into testable evaluation criteria, verify the Axelera stack against them, and maintain a current requirements-versus-capability view across releases, with internal evaluation reports for Automotive, Product and R&D.
•Define and run benchmarks around real automotive use cases (ADAS perception, surround view/parking, BEV/occupancy, DMS/OMS, sensor fusion), expressed in automotive terms (FPS per stream, latency, accuracy at the required operating point).
•Port, quantize and optimize automotive workloads onto Axelera, build reproducible benchmark suites under automotive-realistic conditions, and run competitive comparisons — labeling every result by silicon revision, sample grade and SDK version.
•Maintain benchmark automation, regression tracking and dashboards.
•Identify and close gaps between the current stack and automotive expectations (toolchain, runtime, OS/middleware integration, determinism, diagnostics), and prototype runtime integration into automotive environments (Linux/QNX, AUTOSAR Adaptive, Android Automotive OS, ROS 2).
•Feed automotive-specific requirements and thermal/duty-cycle profiles into SDK/product roadmaps and functional safety work.
•Contribute hands-on to the ASIL-B/ASIL-D software stack (safety runtime, diagnostics, monitoring) alongside R&D and the Functional Safety Manager, verifying it against realistic customer integration scenarios.
•Assess integration effort for a Tier-1/OEM and feed gaps back as prioritized findings.
•Own or co-own technical work packages in collaborative R&D projects and automotive/edge-AI consortia — deliverables, milestones, demonstrators — coordinating with OEM/Tier-1/research partners and keeping the work aligned with the internal roadmap.
•Track automotive AI/ADAS trends and competitive benchmarks, and translate findings into prioritized recommendations for Product and Engineering.

AutomotiveEdge AIEmbedded SoftwareASILSemiconductorBenchmarkingR&DHybridFull-timeEngineering