Job Description
Position - ADAS Embedded Software Engineer
Experience: 4-7 Years
Education: B.E./B.Tech. /M. Tech. in Electronics, Embedded Systems, Computer Science, or a related field.
Job Summary
We are seeking an experienced Senior ADAS Embedded Software Engineer with strong expertise in embedded systems, automotive software development, and AI deployment on embedded platforms. The ideal candidate will have hands-on experience in developing and optimizing ADAS solutions on Renesas R-Car platforms,
working across embedded Linux, BSPs, device drivers, and neural network acceleration frameworks.
Key Responsibilities
Design, develop, and optimize embedded software solutions for ADAS and automotive applications.
Perform SoC bring-up, BSP integration, and board-level software customization for embedded platforms.
Develop and maintain Linux device drivers and embedded Linux software
components.
Configure and manage Yocto-based Linux build environments.
Deploy, optimize, and validate neural network models on embedded AI
accelerators such as Renesas DRP-AI.
Perform model optimization, quantization, and inference tuning to meet real-time automotive performance requirements.
Analyze system performance, memory utilization, and CPU/GPU/accelerator efficiency using profiling and debugging tools.
Collaborate with system architects, AI engineers, and cross-functional teams to deliver production-quality automotive software.
Ensure compliance with automotive software development standards and
coding guidelines, including MISRA C/C++.
Required Technical Skills
Embedded Software Development
Strong programming skills in Embedded C/C++.
Good understanding of automotive-grade software development and MISRA
C/C++ guidelines.
Experience in SoC bring-up, BSP integration, and board support customization.
Hands-on experience with Linux device driver development.
Strong knowledge of the Yocto Build System and embedded Linux
environments.
AI / ADAS Development
Experience deploying neural network models on embedded accelerators such as
DRP-AI on Renesas R-Car V Series platforms.
Strong understanding of DNNs, CNNs, and AI inference optimization.
Hands-on experience with:
o ONNX
o TensorFlow Lite
o Model Quantization (INT8, FP16)
Familiarity with AI model conversion, deployment, and performance
optimization workflows.
Performance Optimization
Experience with real-time performance profiling and debugging tools.
Ability to optimize inference latency, memory footprint, and throughput for
embedded platforms.
Processor & Architecture Knowledge
Strong understanding of ARM Architecture.
Knowledge of:
o Cache management
o Memory hierarchy
o Multi-core processing
o NEON Intrinsics and SIMD optimizations
Preferred Skills
Experience with ADAS perception pipelines and automotive vision systems.
Exposure to camera, radar, or sensor integration in automotive platforms.
Familiarity with AUTOSAR Adaptive, functional safety concepts, or automotive
development processes.
Experience working with Renesas R-Car V3H, V4H, or related R-Car platforms.
Key Competencies
Strong analytical and debugging skills.
Excellent problem-solving and performance optimization capabilities.
Ability to work independently and in cross-functional global teams.
Strong communication and stakeholder management skills.
Location: Bangalore (BLR)
embedded linux,embedded linux software,embedded system,automotive software development,
