Hardware Senior Design Verification Engineer
FuriosaAI
Hardware Senior Design Verification Engineer
FuriosaAI
Power-efficient AI inference accelerator chips
FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon.
Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise.
Define, plan, and implement block and system level verification strategies
Write and review test plans, develop test harnesses and test sequences
Drive the design verification process to successful closure by meeting defined verification metrics across the test plan, functional coverage, and code coverage
Collaborate closely with the Design team to debug, root-cause, and resolve functional failures within the design
Work collaboratively with cross-functional teams, including Design, Model, Emulation, and Silicon Validation, to ensure the highest standards of design quality
Bachelor's degree in Electrical Engineering, Computer Science, or a closely related technical field
5+ years of experience in block and system level verification utilizing SystemVerilog/UVM-based methodologies
Proven experience with Electronic Design Automation (EDA) tools and proficiency in scripting languages (Python, Perl, Shell) for developing verification tools and flows
Experience in architecting and deploying Design Verification infrastructure, including executing the complete verification cycle from planning to closure
Master’s degree in Electrical Engineering, Computer Science, or a closely related technical field
Expertise in developing UVM-based verification environments from initial setup
Expertise in developing Python-based verification environment such as cocotb
Experience in IP or integration verification for high-speed interfaces such as PCIe, UCIe, UALink, and Ethernet
Experience verifying ARM/RISC-V-based sub-systems or SoCs
Strong Python programming skills
Excellent written and verbal communication skills
The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up.
With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion.
At Furiosa, you will:
Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI.
Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks.
Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS.
Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC.
Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition.
FuriosaAI develops AI accelerators for data centers. Its flagship RNGD chip is a power-efficient accelerator designed to boost performance per watt for running large language models and other demanding AI workloads. The hardware is configurable with multiple processing elements to fit different workloads, and it is paired with advanced compiler technology and profiling tools to identify bottlenecks and optimize efficiency. This combination of flexible hardware and software optimization differentiates FuriosaAI from competitors, focusing on maximizing performance while keeping energy use low. The company targets data centers and enterprises that need high-performance, energy-efficient AI solutions, and aims to make AI computing more sustainable and scalable by selling its chips and related software tools and pursuing long-term contracts with large-scale customers.
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