Sr Staff Application Engineer
Renesas Electronics7 hours ago
Responsibilities
- Define and own AI/ML technology architectures for 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 reusable AI frameworks, software architectures, inference pipelines, model-deployment methodologies, and reference implementations.
- Lead 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, and multimodal AI systems.
- Drive hardware/software partitioning across MCUs, MPUs, AI accelerators, NPUs, DSPs, FPGAs, and cloud resources.
- Define efficient AI workload deployment strategies for resource-constrained embedded platforms.
- Evaluate and optimize AI models for accuracy, latency, memory footprint, power consumption, and cost.
- Collaborate with product groups, software teams, system architects, research partners, and strategic customers.
- Provide mentoring and technical leadership to engineering teams across the organization.
- Contribute to AI reference architectures, technical papers, application notes, patents, and ecosystem initiatives.
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.
- 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, 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. in a related discipline, patented AI technologies or algorithms, relevant publications, foundation-model, multimodal AI, or agentic-AI experience, embedded AI deployment, semiconductor architecture familiarity, and experience across industrial automation, automotive, healthcare, robotics, aerospace, IoT, or consumer electronics.
Benefits
- Competitive benefits package alongside salary.
- Regular PERM employment.
- Remote work is not available.
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.