Key Responsibilities

● AI Model Optimization: Tune and optimize pre-trained deep learning models (CNN, YOLO, etc.) for inference on R-CAR SoCs; balance accuracy, latency, and memory footprint.

● Embedded Deployment: Port ML models to R-CAR using frameworks (TensorFlow Lite, ONNX Runtime, or vendor-specific tools); validate edge deployment constraints.

● Performance Tuning: Profile and optimize model inference on R-CAR hardware; leverage HW accelerators (GPU, ISP, VPU) when available.

● ADAS Integration: Implement FCW, DMS, and SVS pipelines; integrate computer vision preprocessing, model inference, and post-processing.

● Firmware & Driver Integration: Work with firmware teams on sensor drivers, ISP pipelines, and real-time scheduling; ensure determinism and safety compliance.

● Testing & Validation: Unit tests, regression testing, functional validation on R-CAR hardware; document performance baselines.

● Automotive Standards: Maintain ASIL/ISO 26262 safety awareness; follow MISRA C++ coding standards; contribute to ASPICE and AUTOSAR alignment.

Required Experience

Total Experience: 5–8 years in embedded systems, automotive software, or related domains.

R-CAR Platform (3–4 years):

● Hands-on experience with Renesas R-CAR Gen3 or Gen4 (H3, H4, M3, M4, or equivalent).

● Familiarity with R-CAR BSP, board support packages, Yocto/BitBake build systems.

● Experience with R-CAR tools: Renesas IDE, Debug Tool, or equivalent.

AI/ML on Embedded Systems:

● Proven track record optimizing neural networks for edge deployment (quantization, pruning, knowledge distillation).

● Experience with at least one ML framework: TensorFlow Lite, ONNX Runtime, PyTorch, or vendor-specific tools (e.g., Renesas e2studio ML tools).

● Understanding of model inference optimization techniques: fixed-point arithmetic, channel-wise optimization,



layer fusion.

C++ & Software Engineering:

● Robust C++ (C++11 or later); clean code, design patterns, memory management.

● Cross-compilation, embedded Linux development, kernel driver basics.

● Version control (Git), testing frameworks, CI/CD pipelines.

Computer Vision & ADAS:

● Familiarity with OpenCV, image preprocessing, or ISP pipelines.

● Understanding of FCW, DMS, or SVS use cases; sensor fusion concepts (camera + radar).

● Real-time constraint awareness; scheduling and synchronization in safety-critical systems.

Automotive Standards:

● ISO 26262 (ASIL) or IEC 61508 awareness.

● MISRA C++ coding guidelines.

● AUTOSAR or similar automotive architecture familiarity.

Technical Skills

Languages: C++, Python, Shell scripting

ML Frameworks: TensorFlow Lite, ONNX, PyTorch, or Renesas ML tools

Platforms: Renesas R-CAR, ARM Cortex-A/M, Linux, RTOS

Tools: GCC, GDB, Valgrind, Trace32, CANoe, Vector tools

Vision & ADAS: OpenCV, image processing, camera calibration, sensor fusion

Build & CI: Yocto, BitBake, CMake, Make, Jenkins, GitHub Actions

Standards: ISO 26262, MISRA C++, ASPICE, AUTOSAR basics

Nice-to-Have

● Experience with Renesas AI Accelerator (DRP-AI) or similar HW acceleration blocks.

● Published work or contributions to open-source ML/embedded projects.

● Automotive OEM or Tier-1 supplier background (camera supplier, safety systems).

● Profiling & optimization tools: Instruments, Perf, ARM MAP.

● Container experience (Docker) for model training pipelines.

Qualifications

● Bachelor’s degree in computer science, Electrical Engineering, or related field (or equivalent industry experience).

● Certifications (Optional): Automotive or ML-related certifications a plus.

Pay: ₹1,800,000.00 - ₹2,000,000.00 per year

Application Question(s):

- R-CAR Experience?

Work Location: In person

📌 Senior C++ Engineer R-CAR AI (India)
🏢 Inspity It Solutions
📍 India