We're looking for a Senior Emulation Engineer to join our hardware verification team. In this role, you'll own the emulation environment for our next-generation NPU — from platform bring-up to full-system integration — and play a critical part in getting silicon right before tape-out. You'll work across time zones with engineers in Korea and the US, and have a direct impact on the quality and schedule of our most complex SoCs to date.
What You'll DoNPU Emulation & Bring-up: Bring-up of next-generation NPUs on emulation platforms. Root-cause complex system-level test failures and resolve emulator environment challenges.
Emulation Interface & Memory Integration: Enable full-system NPU testing by integrating and bringing up high-speed protocol models (PCIe, Ethernet) and advanced memory subsystems (HBM/DDR) within the emulation environment.
Emulation Platform Expertise: Extensive, hands-on experience in developing, compiling, and deploying large-scale emulation models using industry-leading platforms such as Synopsys ZeBu and Cadence Palladium.
Domain Knowledge: Deep technical understanding of AI accelerator architectures (NPU), along with expertise in one or more of the following: interconnect buses, high-speed I/O protocols (PCIe, Ethernet), and advanced memory interfaces (LPDDR, HBM).
Strategic Verification Leadership: Demonstrated ability to define comprehensive emulation strategies, formulate detailed test plans, and drive verification execution for large-scale, complex SoCs.
8+ years of industry experience in hardware emulation or system-level verification.
Bachelors or Masters degree in Electrical Engineering, Computer Engineering, Computer Science, or a related engineering field.
Strong domain knowledge of AI accelerator architectures (NPU), interconnect buses, high-speed I/O protocols (PCIe, Ethernet), and advanced memory interfaces (LPDDR, HBM).
Ability to take initiative and work independently in a cross-regional environment, collaborating effectively across different time zones (Korea and US).
Track record of writing production-grade, meticulous test plans
Strong foundational knowledge of networking protocols
Skills Required
- 8+ years of industry experience in hardware emulation or system-level verification.
- Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related engineering field.
- Extensive hands-on experience developing, compiling, and deploying large-scale emulation models using Synopsys ZeBu and Cadence Palladium.
- Deep technical understanding of AI accelerator architectures (NPU).
- Expertise with interconnect buses, high-speed I/O protocols (PCIe, Ethernet), and advanced memory interfaces (HBM, DDR, LPDDR).
- Demonstrated ability to define emulation strategies, formulate detailed test plans, and drive verification for large-scale SoCs.
- Ability to take initiative and work independently across time zones (collaborating with teams in Korea and the US).
- Track record of writing production-grade, meticulous test plans.
- Strong foundational knowledge of networking protocols.
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.
