What are the responsibilities and job description for the Head of AI position at Architect?
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
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.
- Competitive salary and equity stake
- Fast-paced startup with autonomy and visible impact
- Cutting-edge AI-driven chip design challenges