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Member of Technical Staff - Applied AI

Architect Labs · On-site

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Last seen by MeritLog September 9, 2026Source: AshbySource version: ashby-public-job-posting-v1

Source: the employer's Ashby job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
On-site
Salary
Not listed by source
Location
Palo Alto

What the role asks for

What they're asking for

  • Degree: MS or PhD in Electrical Engineering, Computer Engineering, EECS, or a closely related field.Education
  • 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.Skill
  • 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.Skill
  • Builder Mindset: Demonstrated ability to own ambiguous problems end to end, prototype quickly, and productionize what works. Pragmatic, not precious.Skill
  • 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.Skill
  • Prior experience on AI-for-chip-design or AI4EDA efforts at Google, NVIDIA, or at chip / EDA companies.SkillPreferred
  • Experience building, using, or evaluating LLM-based tooling for engineering workflows.SkillPreferred
  • Publications or open-source contributions at the intersection of ML and EDA (DAC, ICCAD, DVCon, MLCAD, NeurIPS, ICLR, ICML).SkillPreferred
  • Experience as an early engineer at a deeptech or AI startup.SkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

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

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