AA
Automotive Application Engineer
Axelera AI
Contract type
Ongoing
Work mode
On-site · On-site (see listing for address)
Experience
Senior · 6+ years
Job description
Key details
- 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
- Company mission
- Information not specified
Primary stack
Core technologies
Python (Programming Language)
Benefits
- Information not specified
Requirements & details
- 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 an 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 the 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)
- Python, PyTorch, ONNX, AUTOSAR, QNX, Linux, ROS 2, Android Automotive OS, SOME/IP, DDS, MIPI CSI-2
- Python (Programming Language)