4 часа назад
Design Verification Intern (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Design Verification Intern (AI): Verifying custom ASIC IPs including systolic arrays, DMA engines, and NoCs for robust, high-performance, silicon-ready inference hardware with an accent on SystemVerilog, UVM, test benches, and full-stack hardware-software validation. Focus on designing verification environments, validating correctness and performance, and solving complex challenges across RTL, architecture, software, firmware, and emulation.
Location: On-site at the office in San Jose, California
Company
develops custom AI inference hardware by co-designing chips, racks, software, and manufacturing systems for high throughput and low latency.
What you will do
- Verify custom IPs powering ASICs, including systolic arrays, DMA engines, and NoCs.
- Validate hardware correctness and performance across the full hardware-software stack.
- Collaborate with architects, RTL designers, and software, firmware, and emulation teams.
- Develop verification work and write test benches for silicon-ready designs.
- Contribute to inference-focused frontier AI hardware and related research.
Requirements
- Progress toward a Bachelor's, Master's, or PhD degree in electrical engineering, computer engineering, or a related field.
- Familiarity with high-speed digital logic and ASIC or SoC design concepts.
- Familiarity with SystemVerilog, UVM, or Python.
- Familiarity with verification work, test benches, and physical design flows and tooling.
- Ability to learn quickly about transformers and modern artificial intelligence.
Nice to have
- Familiarity with modern ML and LLM model architectures.
- Experience with UVM or formal verification.
- Programming ability in Python or another scripting language.
Culture & Benefits
- 12-week paid internship.
- Generous housing support for relocating interns.
- Daily lunch and dinner at the office.
- Direct mentorship from experienced engineers and industry leaders.
- Fully in-person, cross-disciplinary engineering and research environment.
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