Senior Staff Application Technology Architect – Artificial Intelligence & Machine Learning
Renesas Electronics7 hours ago
Responsibilities
- Define and own AI/ML architectures across 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.
- Develop reusable AI frameworks, software architectures, inference pipelines, model deployment methodologies, and reference implementations.
- Lead evaluation 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, and multimodal AI systems.
- Drive hardware/software partitioning across MCUs, MPUs, AI accelerators, NPUs, DSPs, FPGAs, and cloud resources.
- Optimize AI models and deployment strategies for accuracy, latency, memory footprint, power consumption, and cost on resource-constrained platforms.
- Collaborate with product groups, software teams, system architects, strategic customers, and research partners to integrate AI capabilities.
- Support customer engagements as a trusted advisor on AI architecture and deployment.
- Monitor AI/ML research and identify opportunities for product differentiation and innovation.
- Contribute to reference architectures, technical papers, application notes, patents, and ecosystem initiatives.
- Provide mentoring and technical leadership to engineering teams across the organization.
Requirements
- 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 experience 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, computer vision, sensor analytics, data fusion, pattern recognition, predictive analytics, time-series analysis, explainable AI, and edge AI.
- Strong experience with PyTorch, TensorFlow, ONNX, ML model optimization, data pipelines, and AI deployment frameworks.
- Strong understanding of embedded systems, edge computing platforms, heterogeneous compute architectures, MCUs, MPUs, NPUs, DSPs, AI accelerators, and performance, power, and memory optimization.
- Preferred qualifications include a Ph.D., patented AI technology experience, relevant publications, foundation-model, multimodal AI, and agentic-AI experience, embedded AI deployment experience, semiconductor and AI acceleration familiarity, and cross-industry experience.
Benefits
- Regular PERM employment; remote work is not available.
- Competitive benefits package provided alongside salary; further details are provided during the hiring process.
Tech Stack
PyTorchTensorFlow
Categories
About Renesas Electronics
Renesas Electronics designs and sells microcontrollers, analog and power ICs, and connectivity solutions for automotive, industrial, infrastructure and IoT manufacturers. Its portfolio spans embedded processing, power management and ADAS-ready components, sold directly and through channels to OEMs and Tier-1 suppliers, with software and development tools to integrate them. Founded in 2010 and headquartered in Tokyo, it is a public company on the Tokyo Stock Exchange and has expanded through acquisitions including Intersil and Dialog Semiconductor.