We are pleased to announce positions for System Architects who will build end-to-end applications, making use of the revolutionary AI engines embedded in our SoCs. Your AI applications will drive ultra low-power devices in the remotest corners of the internet-of-things.
You will bring proven experience in architecting robust solutions on edge devices, such as security cameras, drones, cars, home automation systems, etc. These solutions could range from e.g. heart-rate monitoring to video analytics and autonomous driving. Experience with artificial intelligence is appreciated, but not required.
As a leading member of the engineering team, you will be responsible for the architecture descriptions and documentation of artificial intelligence and machine learning applications, software stacks, and artificial intelligence silicon IPs.
The System 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 define the key performance and power metrics to which these solutions need to adhere. In order to predict and measure these key performance metrics, you will develop analysis tools, such as performance simulators. 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 neural network design and programming 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, Neuroscience, Electrical Engineering, or related field;
- 5+ years of experience in the fields of media and/or signal processing applications;
- Experience in architecting end-to-end solutions, consisting of both software and hardware;
- 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 with common requirements management practices;
- Good understanding of hardware development and software development practices.