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FuriosaAI designs high-performance, power-efficient AI accelerators (NPUs) used in data centers for computer vision, GenAI, LLMs, and demanding workloads.

About FuriosaAI

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.

 

About the Role

FuriosaAI의 Silicon Validation 팀은 테이프아웃(Tape-out) 전후의 NPU 칩이 시스템 레벨에서 완벽하게 동작하도록 검증하는 핵심 부서입니다. 설계(RTL/DV)와 소프트웨어(FW/OS) 사이의 징검다리로서, 체계적인 검증 방법론을 바탕으로 1st Silicon Bring-up부터 NPU의 성능 최적화 및 시스템 안정성 확보까지 칩 상용화의 전 과정을 주도합니다.

Key Responsibilities

  • NPU 1st Silicon Bring-up 주도: NPU 가속기 코어, CPU Subsystem, NoC(Network-on-Chip) 등 주요 컴퓨팅 및 대용량 데이터 인터커넥트 블록의 초기 구동 및 시나리오 기반 기능 검증, Memory Subsystem(LPDDR/HBM 등) 및 High-Speed I/F(Ethernet 등) 연동 검증, Board Bring-up 및 시스템 초기화 (Booting Sequence, Clock/Reset configuration)

  • 체계적인 Validation 방법론 수립 및 실행: Pre-silicon (Emulator, FPGA) 및 Post-silicon 환경에서의 검증 계획(Test Plan) 수립 및 커버리지 관리, 각 IP 검증을 위한 Test Firmware (Bare-metal) 작성 및 시나리오 개발

  • System-level Issue Debugging & Workaround 도출: HW(RTL)와 SW(Firmware/Driver) 경계에서 발생하는 복합적인 이슈 원인 분석 (JTAG, Trace32 등 활용), 문제 해결을 위한 Workaround 솔루션 도출 및 유관 부서 리포팅

  • Performance Validation & Optimization: NPU 데이터 처리 파이프라인 및 메모리 대역폭 성능 최적화 검증 지원

  • Test Automation (테스트 자동화): 검증 효율성을 높이기 위한 자동화 스크립트 작성 및 CI/CD 연동 검증 환경 구축

Minimum Qualifications

  • Validation Team Leadership and Planning: NPU 세대별 브링업 및 검증 로드맵 기획, 일정 관리

  • Cross-functional Communication: Design, DV, Firmware, Software, QA 등 유관 부서와의 협업 조율 및 기술적 의사결정 주도

  • Team Building and Mentoring: 팀원들의 기술 역량 향상 리딩 및 체계적인 검증 프로세스(Methodology) 정착

  • Experience: SoC, ASIC, 또는 복잡한 Silicon Validation / System Validation 업무 경험자 (리더급의 경우 해당 분야 리딩 경험 또는 그에 준하는 시니어 경력 필수)

  • Architect Knowledge: ARM Architecture, AMBA BUS (AXI, AHB 등) 및 전반적인 SoC/컴퓨터 구조에 대한 높은 이해도

  • Programming: 하드웨어 제어 및 IP 테스트를 위한 Embedded C/C++ 및 Rust 프로그래밍 역량 (Bare-metal 환경 개발 경험)

  • Validation Methodology: Test Plan 수립부터 Bug Tracking, Coverage 확보에 이르는 체계적인 Validation Methodology에 대한 이해 및 경험

  • Debugging Expertise: JTAG 디버거(Trace32 등) 활용 능력 및 HW/SW Co-debugging 역량

  • Problem Solving: 복잡한 시스템 이슈를 논리적으로 분석하고 끈기 있게 추적하여 해결할 수 있는 문제 해결 능력

Preferred Qualifications

  • AI 가속기(NPU, TPU) 또는 GPU, 복잡한 멀티코어 SoC 검증 및 Bring-up 경험이 있으신 분

  • Pre-silicon (Palladium, Zebu, FPGA 등) 환경에서의 Validation 경험이 있으신 분

  • Ethernet, CXL, LPDDR, HBM 등 High-Speed Interface의 프로토콜 및 컨트롤러 동작 수준에 대한 이해도가 높으신 분

  • Linux Kernel / Device Driver 동작 원리에 대한 이해가 있으신 분

  • 시스템 수준의 소프트웨어 개발에서 Rust 언어를 적극적으로 활용해 본 경험이 있으신 분

  • Python, Tcl, Bash 등 스크립트 언어를 활용한 검증 자동화 환경 구축 경험이 있으신 분

Why Join FuriosaAI

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. 

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