Designs and implements cloud native AI hardware infrastructure from scratch, including power, network architecture, storage, and bare-metal operating systems.
Designs and implements scalable softawre defined network architecture
Designs, implements, and operates multi-regional on-premise Kubernetes clusters using programmable networks and bare-metal as a service.
Designs, implements, and operates multi-cloud Kubernetes clusters (AWS, GCP, Azure, etc.) without vendor lock-in.
Designs and implements zero-trust networks, including authentication, authorization, and auditing for development environments.
Bachelor’s degree in Computer Science or equivalent work experience.
Strong communication skills for requirement gathering and clarification.
3+ years of experience in programming with Rust, Python, Golang, C, or C++.
3+ years of experience designing and developing core components of cloud-native infrastructure, such as networking, storage, monitoring systems, and bare-metal as a service.
Strong background in foundational technologies, including storage and networking.
Experience in developing low-level systems, such as the Linux kernel and distributed systems.
Hands-on experience with cloud ecosystems, including Kubernetes and OpenStack.
Top Skills
What We Do
FuriosaAI designs and develops data center accelerators for the most advanced AI models and applications.
Our mission is to make AI computing sustainable so everyone on Earth has access to powerful AI.
Our Background
Three misfit engineers with each from HW, SW and algorithm fields who had previously worked for AMD, Qualcomm and Samsung got together and founded FuriosaAI in 2017 to build the world’s best AI chips.
The company has raised more than $100 million, with investments from DSC Investment, Korea Development Bank, and Naver, the largest internet provider in Korea. We have partnered on our first two products with a wide range of industry leaders including TSMC, ASUS, SK Hynix, GUC, and Samsung. FuriosaAI now has over 140 employees across Seoul, Silicon Valley, and Europe.
Our Approach
We are building full stack solutions to offer the most optimal combination of programmability, efficiency, and ease of use. We achieve this through a “first principles” approach to engineering: We start with the core problem, which is how to accelerate.
