Additionalinformation

Additional Information

Nice to Have

• PhD in Applied Mathematics, Machine Learning, Signal Processing, Computer Vision, or related discipline

• Experience developing patented AI technologies or algorithms

• Publications in AI, machine learning, signal processing, or computer vision

• Experience with foundation models, multimodal AI, and agentic AI systems

• Experience with sensor analytics and anomaly detection

• Experience in embedded AI deployment

• Familiarity with semiconductor architectures and AI acceleration technologies

• Industry experience spanning multiple domains such as industrial automation, automotive, healthcare, robotics, aerospace, IoT, or consumer electronics

Renesas is an embedded semiconductor solution provider driven by its Purpose, To Make Our Lives Easier. With a global team of over 21,000 engineers and problem solvers in more than 30 countries, we offer the opportunity to work on world‑leading 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.

Renesas Electronics deals with dual-use technology that is subject to U.S. export controls regulations. Under these regulations it may be necessary for Renesas to obtain U.S. government export license prior to release of technology to certain persons. The decision whether or not to file or pursue an export license application is at the sole discretion of Renesas.

Companydescription

Company Description

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Jobdescription

Job Description

About the Role

We are looking for an experienced and visionary Edge AI Architect to define, drive, and evolve artificial intelligence and machine learning technologies across a broad range of intelligent embedded and edge computing solutions.

In this role, you will serve as a technical authority for AI and machine learning, bridging advanced algorithms, sensor analytics, edge computing, and semiconductor technologies. You will collaborate with product groups, system architects, software teams, and strategic customers to develop innovative AI-enabled solutions that deliver differentiated value across multiple market segments.

Your work will help shape the company's AI strategy, accelerate adoption of edge intelligence, and enable next-generation intelligent systems through advanced machine learning, signal processing, perception, and data analytics technologies.

Key Responsibilities

• Define and own AI/ML technology architectures spanning embedded systems, edge computing, cloud-connected systems, and intelligent sensor solutions.

• Translate customer challenges, market opportunities, and technology trends into AI solution architectures and technology roadmaps.

• Drive development of reusable AI frameworks, software architectures, inference pipelines, model-deployment methodologies, and reference implementations.

• Lead the evaluation, development, and adoption of machine learning, deep learning, foundation-model, and agentic-AI technologies.

• Define architectures for:

• Sensor intelligence

• Signal processing

• Computer vision

• Anomaly detection

• Predictive analytics

• Sensor fusion

• Autonomous decision making

• Multimodal AI systems

• Drive hardware/software partitioning across MCUs, MPUs, AI accelerators, NPUs, DSPs, FPGAs, and cloud resources.

• Define efficient deployment strategies for AI workloads on resource-constrained embedded platforms.

• Evaluate and optimize AI models for accuracy, latency, memory footprint, power consumption, and cost.

• Collaborate closely with product groups, software teams, system architects, and research partners to integrate AI capabilities into future solutions.

• Support strategic customer engagements and act as a trusted advisor on AI architecture and deployment.

• Monitor advances in AI/ML research and identify opportunities for product differentiation and innovation.

• Contribute to AI reference architectures, technical papers, application notes, patents, and ecosystem initiatives.

• Provide mentoring and technical leadership to engineering teams across the organization.

Qualifications

• Master's or Ph.D. degree in Computer Science, Applied Mathematics, Artificial Intelligence, Electrical Engineering, Physics, Data Science, or a related field.

• 10+ years of experience in AI/ML, advanced analytics, signal processing, computer vision, or intelligent embedded systems.

• Proven track record as an AI Architect, Principal AI Engineer, Chief Architect, AI Research Lead, or equivalent technical leadership role.

Proven Expertise In: Machine Learning, Deep Learning, Statistical Modeling, Signal Processing, Computer Vision, Sensor Analytics, Data Fusion, Pattern Recognition, Predictive Analytics, Time-Series Analysis, Explainable AI, Edge AI

Strong Experience With: PyTorch, TensorFlow, ONNX, ML model optimization, Data pipelines, AI deployment frameworks

Strong Understanding Of: Embedded systems, Edge computing platforms, Heterogeneous compute architectures, MCUs, MPUs, NPUs, DSPs, and AI accelerators, Performance, power, and memory optimization

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