About Architect

Architect is an AI research and product lab for chip design. We build AI models and systems that can explore, design, optimize, and verify new hardware. Our goal is to reimagine chip design using AI, cut down ASIC design time and cost, and enable a new era of ultra-efficient, domain-specific chips powering the future of computation.

Born out of Stanford, our team blends researchers and engineers from DeepMind, Meta, Apple, Intel, and other frontier labs. Backed by leading VCs and angels, including the Chief Scientist at Google, Stanford professors, and founders of chip companies, Architect operates in stealth, pushing the limits of AI4EDA and building the intelligence layer for the hardware revolution.

What You’ll Do

We’re looking for a visionary and hands-on AI leader to shape the future of intelligence in chip design. At Architect, you’ll work alongside the founders to define and execute the ML roadmap for next-generation AI models and systems that rethink how silicon is built, from first-principles. You’ll lead, mentor, and scale a world-class team of ML engineers and researchers, setting the standard for innovation across code generation, verification, reasoning and multimodal capabilities. This is a rare opportunity to help train novel AI models and agent-based systems, push the limits of ML4EDA, and pioneer breakthroughs at the intersection of machine learning, reinforcement learning, and chip design.

What We’d Like to See

• Degree: PhD in Computer Science, EECS, Mathematics, or a closely related field. Preferably, specialization in Machine Learning, Deep Learning or Artificial Intelligence. Or BS/MS with very strong industry research engineering experience.

• Background: We don't expect candidates to have any chip design background. Rather we would prefer candidates with strong ML background with an interest to apply that to hardware design.

• Hands-On Experience:

• • Strong industry or research background in leading engineering teams, building end-to-end ML pipelines, training models and building multi-agent systems.
  • 5+ years of industry experience in frontier labs or high-growth AI startups; 8 yrs+ strongly preferred.

• Core Skills:

• • Deep expertise in reinforcement learning, self-supervised learning, SFT, and multi-agent systems.
  • Experience building verifiers, reward functions, and agentic environments.
  • Fundamental understanding of modern model architectures, scaling laws, and steering data towards a training objective.
  • Publications in top ML (NeurIPS, ICLR, ICML) or EDA (DAC, ICCAD, DVCon) venues
  • End-to-end model training, especially owning the training recipe, data recipe, and RL post-training workflows
  • Multi-agent orchestration, context management, prompt optimization, inference/test-time scaling
  • Ability to move fast, prototype, and scale research into production.
  • Obsession with pushing state-of-the-art performance in real-world constraints.
  • Ability to lead and build teams, set engineering standard and b

• Systems Knowledge: Comfortable with cloud-native architectures and distributed systems.

• Bonus:
• • Prior experience in frontier labs, training LLMs at scale. Bonus if worked on post-training, RL, Synthetic Data, Code Generation etc.
  • Prior experience in AI-for-chip-design experience at NVIDIA, DeepMind, Synopsys, Cadence, etc.
  • Foundation in Electrical/Computer Engineering and chip-design or verification processes.

What We Offer

• Competitive salary and equity stake
• Fast-paced startup with autonomy and visible impact
• Cutting-edge AI-driven chip design challenges