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Role description 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. Robust 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. Solid 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) Skills embedded linux,embedded linux software,embedded system,automotive software development, About UST UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the worlds best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients organizations. With over 30,000 employees in 30 countries, UST builds for boundless impacttouching billions of lives in the process. .
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In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.