Senior Staff Application Engineer

Job Title

Senior Staff Application Engineer

Role Summary

Technical lead responsible for defining AI/ML architectures and driving deployment of edge and embedded intelligence across products and customer engagements. Works with product teams, system architects, software groups, and customers to create reusable frameworks, reference implementations, and technology roadmaps for AI-enabled embedded systems.

Experience Level

Senior - requires significant technical leadership. The posting specifies 10+ years of experience in AI/ML, signal processing, computer vision, or intelligent embedded systems.

Responsibilities

Primary responsibilities focus on architecture, model deployment, and technical leadership for embedded and edge AI solutions.

• Define and own AI/ML architectures across embedded, edge, cloud-connected, and sensor systems.
• Translate customer problems and market trends into solution architectures and technology roadmaps.
• Drive development of reusable AI frameworks, inference pipelines, deployment methodologies, and reference implementations.
• Lead evaluation and adoption of machine learning, deep learning, foundation models, and agentic-AI technologies.
• Architect systems for sensor intelligence, signal processing, computer vision, anomaly detection, predictive analytics, sensor fusion, and multimodal AI.
• Specify hardware/software partitioning across MCUs, MPUs, NPUs, DSPs, FPGAs, AI accelerators, and cloud resources.
• Define efficient deployment strategies and optimize models for accuracy, latency, memory, power, and cost on resource-constrained platforms.
• Collaborate with product groups, software teams, research partners, and strategic customers; provide technical leadership and mentoring.
• Contribute to reference architectures, technical papers, patents, and ecosystem initiatives.

Requirements

Must-have technical skills and experience for this role.

• 10+ years' experience in AI/ML, advanced analytics, signal processing, computer vision, or embedded/edge systems.
• Proven track record as an AI Architect, Principal AI Engineer, Chief Architect, AI Research Lead, or equivalent technical leadership role.
• Expertise in machine learning, deep learning, statistical modeling, signal processing, sensor analytics, data fusion, pattern recognition, predictive analytics, and time-series analysis.
• Strong practical experience with PyTorch, TensorFlow, ONNX, model optimization, data pipelines, and AI deployment frameworks.
• Deep understanding of embedded systems and heterogeneous compute architectures (MCUs, MPUs, NPUs, DSPs, AI accelerators) and performance/power/memory tradeoffs.
• Experience optimizing models for accuracy, latency, footprint, power consumption, and cost on constrained hardware.
• Ability to engage with customers and cross-functional teams to define architectures and deliverable reference implementations.
• Excellent technical communication and mentoring skills.

Education Requirements

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

About the Company

Company: Renesas

Headquarters: Hitachinaka, Japan

Renesas is a global leader in embedded semiconductor solutions, providing high-quality products across automotive, industrial, infrastructure, and IoT sectors. With over 22,000 employees in more than 30 countries, the company focuses on scalable solutions that enhance user experience and drive innovation while committed to sustainability and energy efficiency.