We are pleased to announce positions for SoC Architects to lead our chip design developments, making use our revolutionary embedded artificial intelligence engines. Your SoCs will drive ultra low-power AI processing in devices in the remotest corners of the internet-of-things.
You will bring proven experience in architecting complex multi-IP SoCs for edge devices, such as security cameras, drones, cars, home automation systems, etc. Experience with artificial intelligence is appreciated, but not required. You will also bring deep understanding of silicon design processes and flows.
As a leading member of the engineering team, you will be responsible for the SoC architecture descriptions and related documentation. You will provide technical guidance to the company’s silicon development. You will drive the development of the company’s SoCs consisting of amongst others multiple artificial intelligence IPs.
The SoC Architect contributes to developing our roadmap for different families of artificial intelligence SoCs, in line with the requirements of various high-growth markets. The roadmaps take into account the technical and physical characteristics and constraints of e.g. silicon implementation processes, software development, and optimization techniques.
You will work together with an infrastructure team that provides the compute, integration, and test reporting resources. You will also work together with tooling teams that develop automated hardware construction tools. And you will work with application teams, both internal and with customers, who provide key insights on requirements, performance metrics, robustness, and stability of the company’s solutions.
- M.Sc or Phd in Computer Science, Electrical Engineering, or related field;
- 10+ years of experience in the field of product SoC design, including sourcing of (hardware) IP libraries on advanced silicon nodes;
- Experience with driving digital and/or mixed-signal design flows;
- Demonstrated designs for e.g. imaging, video processing, video analytics, machine learning, etc.
- Experience in technical leadership roles;
- Excellent problem analysis skills;
- Excellent communication skills in English (both speaking and writing).
Nice to have
- Working knowledge of artificial intelligence, deep learning, and/or neuromorphic computing;
- Experience in architecting end-to-end solutions, consisting of both software and hardware;
- Experience with common requirements management practices;
- Good understanding of hardware development and software development practices.