6 часов назад
Hardware Engineer, Architect (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Hardware Engineer, Architect (AI) (Custom AI Silicon): Defining silicon and system microarchitecture for unconventional compute platforms targeting highly efficient LLM and diffusion model inference with an accent on compute tiles, memory hierarchies, and hardware/software co-design. Focus on translating transformer and diffusion workloads into microarchitectural specifications, defending PPA tradeoffs, co-designing the ISA, and validating designs before tapeout.
Location: Silicon Valley, United States; hybrid
Company
develops foundational hardware and software for the semiconductor industry, AI infrastructure, and advanced computing systems.
What you will do
- Define silicon and system microarchitecture for a custom unconventional compute platform targeting LLM and diffusion model inference.
- Design AI accelerator compute blocks, including processing-element arrays, datapaths, sparsity support, and reduced-precision computation.
- Translate transformer and diffusion workloads into hardware specifications covering compute tiles, memory hierarchies, and tile interconnects.
- Build performance models and make full-stack power, performance, and area trade-offs across algorithms, memory, interconnect, and physical design.
- Co-design the instruction set architecture and programming model with the compiler team.
- Direct block-level pre-silicon validation with FPGA design engineers and systems architects, and assess AI accelerator research directions.
Requirements
- Degree in electrical engineering, computer engineering, computer science, or equivalent experience.
- Substantial experience architecting or microarchitecting high-performance digital systems such as AI accelerators or complex compute engines.
- Experience translating workload analysis into datapaths, pipeline stages, and area and power estimates.
- Experience using cycle-accurate or analytical simulation models to guide architecture decisions before RTL implementation.
- Experience with quantization, reduced-precision inference, microarchitecture specifications, and collaboration with RTL engineers.
- Proficiency in Python or C++ and familiarity with SystemVerilog or equivalent RTL.
Culture & Benefits
- Collaborate across hardware, compiler, RTL, analog, FPGA, systems, and research teams.
- Work in an environment where the architecture is actively discovered alongside implementation.
- Participate in research-adjacent work, including reading and potentially publishing research.
- Inclusive equal-opportunity workplace with reasonable accessibility accommodations.
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