Member of Technical Staff Applied AI

Architect is a frontier AI lab for chip design. We build AI models and tools for on-demand custom ASICs at scale. Our goal is to co-design custom ASICs alongside evolving ML workloads and enable a new era of domain-specific chips that unlock capabilities impossible with current hardware paradigms. Born out of Stanford Research our team blends AI with Silicon with a founding team from Anthropic Google DeepMind Meta SuperIntelligence xAI Apple and Intel.

What Youll Do

As a Founding Member of the Technical Staff (Applied AI) at Architect youll sit at the intersection of chip design and frontier AI translating deep hardware engineering expertise into agentic systems that can reason about generate and verify real silicon.

• Design and build AI agents that tackle core chip-design tasks grounding model behavior in how real hardware engineers actually work.

• Own end-to-end agent workflows: scaffolding tool use evaluation harnesses and the domain-specific infrastructure that makes agents useful on actual design problems.

• Serve as the hardware conscience of the model curating high-quality data defining evaluation criteria and encoding the engineering judgment that separates plausible outputs from correct ones.

• Partner closely with the ML research post-training and infra teams to turn hardware domain expertise into reward signals benchmarks and training signal.

• Move fast in a 01 environment: prototype dogfood break things iterate. Translate ambiguous chip-design challenges into concrete agent capabilities that ship.

What Wed Like to See

Qualifications & Skills:

• Degree: MS or PhD in Electrical Engineering Computer Engineering EECS or a closely related field.

• Hardware Background: Strong industry or research experience as an RTL design or Design Verification engineer with a solid understanding of the modern chip design flow end to end.

• Software Engineering: Excellent software engineering fundamentals comfortable writing clean production-grade Python or typescript building tooling and working in modern engineering environments. This is a non-negotiable bar.

• Builder Mindset: Demonstrated ability to own ambiguous problems end to end prototype quickly and productionize what works. Pragmatic not precious.

• Curiosity for AI: Genuine excitement about applying frontier AI to hardware. No prior applied-AI or ML research background is required well meet you where you are.

Bonus:

• Prior experience on AI-for-chip-design or AI4EDA efforts at Google NVIDIA or at chip / EDA companies.

• Experience building using or evaluating LLM-based tooling for engineering workflows.

• Publications or open-source contributions at the intersection of ML and EDA (DAC ICCAD DVCon MLCAD NeurIPS ICLR ICML).

• Experience as an early engineer at a deeptech or AI startup.

What We Offer

• Competitive salary and meaningful equity stake

• Fast-paced startup with autonomy and visible impact

• Cutting-edge AI-driven chip design challenges

Required Experience:

Staff IC