Staff AI Application Engineer (Automotive SoC)

Job Summary

We are looking for an AI Application Engineer to support the enablement optimization and deployment of AI models on automotive-grade SoCs.

In this role you will work closely with internal compiler/runtime teams and external customers to bring AI models from training to optimized inference on embedded NPU/DSP platforms with a strong focus on performance accuracy and system integration.

Key Responsibilities

AI Model Enablement & Optimization

• Enable and deploy AI models (e.g. BEV object detection segmentation classification) on Gen4/5 SoC platforms with CNNIP/DSP/NPU HWA.
• Perform model performance analysis (latency throughput multi-core scaling) and identify bottlenecks related to memory bandwidth scheduling or operator mapping.
• Support model optimization workflows including:
  • Post-Training Quantization (PTQ)
  • Quantization-Aware Training (QAT) collaboration
  • Operator fusion graph optimization and execution partitioning
• Analyze accuracy degradation caused by quantization or operator limitations and propose mitigation strategies.

Embedded AI Inference & System Integration

• Integrate AI models into embedded runtime environments (Linux / QNX).
• Debug issues related to:
  • CNNIP/DSP/NPU offloading
  • Memory allocation / IPMMU
  • Data transfer overhead and multi-core synchronization
• Validate AI workloads on target boards and simulators (SIL / HIL).

Toolchain & Model Workflow Support

• Work with AI compiler and runtime toolchains (e.g. ONNX-based workflows hybrid compiler MWMX).
• Support ONNX model handling including:
  • Graph inspection and modification
  • Model segmentation and execution control
  • Quantized (QDQ) ONNX models
• Develop or maintain internal tools and scripts to improve model validation benchmarking and customer workflows.

Customer & Cross-Team Collaboration

• Act as a technical interface between customers internal development teams and field application engineers.
• Support customer evaluations PoCs and demos on automotive AI platforms.
• Provide technical guidance documentation and best practices for AI model deployment.
• Contribute to weekly technical reports issue tracking and release validation activities.

What We Offer

• Opportunity to work on state-of-the-art automotive AI platforms.
• Hands-on involvement across the entire AI lifecycle from model to silicon.
• Close collaboration with compiler runtime and hardware architecture teams.
• Exposure to real customer deployments and production constraints.

Qualifications :

Required Qualifications

• Bachelors or Masters degree in Computer Science Electrical Engineering Embedded Systems or have experience in embedded systems.
• Solid understanding of deep learning fundamentals and inference pipelines.
• Hands-on experience with AI frameworks such as PyTorch ONNX or ONNX Runtime.
• Strong programming skills in Python; 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.

Preferred / Optional Qualifications

• 13 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.

Nice to Have

• 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.

Additional Information :

Renesas is an embedded semiconductor solution provider driven by its Purpose To Make Our Lives Easier. With a global team of over 21000 engineers and problem solvers in more than 30 countries we offer the opportunity to work on worldleading technology for Automotive Industrial Infrastructure and IoT shaping a safer healthier greener and smarter future.

At Renesas TAGIE is our culture grounded in being Transparent Agile Global Innovative and Entrepreneurial. It shapes how we work grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives.

We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process.

Are you ready to join our team and shape the future with us

Renesas Electronics is an equal opportunity and affirmative action employer committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex race religion national origin gender gender identity gender expression age sexual orientation military status veteran status or any other basis protected by law. For more information please read our Diversity & Inclusion Statement.

Remote Work :

No

Employment Type :

Full-time