Member of Technical Staff - Applied AI

Member of Technical Staff - Applied AI ABOUT ARCHITECT 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 You'll Do As a Founding Member of the Technical Staff (Applied AI) at Architect, you'll 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 0→1 environment: prototype, dogfood, break things, iterate. Translate ambiguous chip-design challenges into concrete agent capabilities that ship. What We'd 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 — we'll 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