Overview
Job description:
You will lead our AI computing and modeling architecture strategy. We are seeking an ambitious and visionary leader with deep technical expertise who is passionate about transforming AI computing for autonomous driving. You will play a pivotal role in architecting, optimizing, and executing a roadmap that supports advanced AI acceleration. Working closely with a team of world-class engineers and scientists, you will drive the development of next-generation ASIC and AI hardware solutions.
Responsibilities:
- Lead the architectural design and development of AI computing architect to meet the needs of autonomous driving and edge AI applications.
- Define and implement technical roadmaps that support cutting-edge AI accelerators for machine learning training and inference.
- Collaborate with software, ASIC, and algorithm teams to ensure the alignment of hardware and software, delivering highly efficient and optimized solutions.
- Stay ahead of industry trends in deep learning, neural network acceleration, and multimedia processing, incorporating key advancements into company strategies.
- Ensure the optimization of hardware architecture for high-efficiency neural network acceleration, including areas such as fixed-point quantization, arithmetic optimization, and scheduling.
Qualifications
Qualifications:
- Master or PhD in Computer Engineering, Electrical Engineering, or a related field.
- Minimum 10 years of experience in AI computing and architectures.
- Proven experience in leading large-scale hardware-software co-design projects for AI computing or SoC architectures.
- Strong knowledge of deep learning algorithms, including CNNs, RNNs, and hardware acceleration techniques.
- Solid understanding of SoC architectures, performance, power, and area (PPA) trade-offs, and micro-architecture design.
- Expertise in embedded programming, firmware development, and hardware optimization for AI workloads.
Ideal Candidate:
- A visionary leader with the technical depth to drive innovation in AI computing and modeling.
- Strong problem-solver who can make critical decisions balancing performance and efficiency in hardware design.
- A motivated individual with a passion for the intersection of AI, deep learning, and hardware acceleration.
