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Axelera AI is seeking a hands-on Automotive Application Engineer to validate and adapt its edge-AI platform—accelerator silicon and software toolchain—against automotive market requirements. You will work within the Automotive team, translating market and customer needs into testable criteria and verifying the solution against them.
Key responsibilities include:
**Solution Validation**: 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.
**Benchmarking**: Define and run benchmarks around real automotive use cases (ADAS perception, surround view/parking, BEV/occupancy, DMS/OMS, sensor fusion). Port, quantize, and optimize automotive workloads onto Axelera; build reproducible benchmark suites under automotive-realistic conditions; run competitive comparisons labeled by silicon revision, sample grade, and SDK version. Maintain benchmark automation, regression tracking, and dashboards.
**Stack Adaptation**: Identify and close gaps between the current stack and automotive expectations (toolchain, runtime, OS/middleware integration, determinism, diagnostics). 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.
**Safety-Qualified Software**: Contribute hands-on to ASIL-B/ASIL-D software stack (safety runtime, diagnostics, monitoring) alongside R&D and the Functional Safety Manager. Assess integration effort for Tier-1/OEM and feed gaps back as prioritized findings.
**Collaborative Programs**: 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.
**Market Intelligence**: Track automotive AI/ADAS trends and competitive benchmarks; translate findings into prioritized recommendations for Product and Engineering.
You will report to the Head of Automotive and work closely with the Principal Automotive Solution Architect, software and AI R&D teams, Product Management, and the Functional Safety Manager.
Axelera AI is a deep-tech company that has raised $450 million in five years and built a team of 250+ employees (60+ PhDs with 40,000+ citations) across 20 countries. The company has launched its Metis™ AI Platform, achieving 3-5x efficiency and performance gains, with a business pipeline exceeding $100 million.
**Requirements:**
Required:
- 4–8 years in embedded software or application engineering in automotive or automotive semiconductors, with strong embedded C and Python for tooling/test automation
- Real-time systems and safety-qualified development in ASIL-B/ASIL-D context (ISO 26262 requirements, safety mechanisms, diagnostics, supporting evidence)
- Embedded development on constrained targets (board bring-up, drivers, BSPs) using standard automotive toolchains (cross-compilation, trace/debug, CI, MISRA), on embedded Linux with exposure to QNX or AUTOSAR
- Validation on target hardware: bench/HIL testing and characterization across the automotive temperature range
- Structured, requirements-to-evidence mindset and clear technical writing
- Fluent English; ~15% travel for consortium meetings and partner labs
Highly Appreciated:
- Exposure to deep-learning frameworks (PyTorch, ONNX), model deployment on embedded targets, and quantization/graph compilation concepts—or appetite to learn quickly
- Familiarity with computer-vision/camera-based automotive perception workloads
- Experience in collaborative R&D projects (Horizon Europe, Chips JU, national programs)
- Deeper experience with AUTOSAR Adaptive, Android Automotive OS, SOME/IP, DDS, or sensor interfaces (MIPI CSI-2, GMSL/FPD-Link)
- Awareness of ISO 21434 and A-SPICE; exposure to vehicle E/E architectures
- An additional European language
Experience with AI is valued but not a prerequisite—the role includes structured ramp-up with direct R&D support.
