Renesas Electronics
Tech / AI / Software
ApplicationEngineer(AutomotiveSoC)
“Application Engineer (Automotive SoC) at Renesas Electronics. Skills: AI Model Enablement & Optimization, Embedded AI Inference & System Integration, Toolchain & Model Workflow Support. Enable and deploy AI models on automotive-grade SoCs. Perform model performance analysis and identify bottlenecks”
What You'll Achieve.
Bring AI models from training to optimized inference on embedded NPU/DSP platforms; Focus on performance, accuracy, and system integration
Industry & Context.
Identify bottlenecks related to memory bandwidth, scheduling, or operator mapping; Analyze accuracy degradation caused by quantization or operator limitations and propose mitigation strategies; Debug issues related to CNNIP/DSP/NPU offloading, Memory allocation / IPMMU, Data transfer overhead and multi-core synchronization
What They're Looking For.
Must Have
Solid understanding of deep learning fundamentals and inference pipelines, Hands-on experience with AI frameworks such as PyTorch, ONNX, or ONNX Runtime, programming skills in working knowledge of C/C++ is a plus, Familiarity with embedded systems and debugging tools, Ability to analyze performance using metrics such as latency, throughput, and hardware utilization, Good communication skills in a multi-cultural, cross-functional environment
Nice to Have
1–3 years of experience in embedded systems or AI-related development, Experience with AI model training, fine-tuning, or evaluation, especially for: Computer vision models (Detection / Segmentation / BEV), Automotive or robotics use cases, Practical experience with AI inference optimization on embedded hardware (NPU, DSP, GPU, or CPU), Familiarity with quantization techniques (INT8, calibration methods, QDQ models), Experience with automotive SoCs or safety-related software environments (QNX is a plus), Understanding of memory hierarchy, DMA, and multi-core scheduling in SoC architectures, Experience supporting customers or acting in a technical support / application engineering role, Knowledge of automotive AI standards or ADAS perception pipelines, Experience contributing to internal tools, scripts, or documentation, Ability to read and debug ONNX graphs or intermediate representations
What You'll Do.
Enable and deploy AI models on automotive-grade SoCs
Perform model performance analysis and identify bottlenecks
Support model optimization workflows
Analyze accuracy degradation and propose mitigation strategies
Integrate AI models into embedded runtime environments
Debug issues related to AI model inference and system integration
Validate AI workloads on target boards and simulators
Work with AI compiler and runtime toolchains
Support ONNX model handling
Develop or maintain internal tools and scripts
Act as a technical interface between customers
internal development teams
and field application engineers
Support customer evaluations
Provide technical guidance
Contribute to weekly technical reports
and release validation activities
How You'll Work.
Team & Collaboration
Work closely with internal compiler/runtime teams and external customers; Act as a technical interface between customers, internal development teams, and field application engineers; Collaborate with QAT teams; Collaborate with field application engineers
Communication Scope
Good communication skills in a multi-cultural, cross-functional environment
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