AI Research Resident

The role

Residents will develop recursive self-improvement strategies and use AI to accelerate hardware design. You will work across hardware and software to build evaluation infrastructure and drive original technical investigations.

What you will do

• Develop recursive self-improvement strategies.
• Apply AI to accelerate hardware design.
• Use hardware advances to accelerate AI itself.
• Build the evaluation infrastructure this loop needs.
• Drive a research question of your own.
• Co-author a paper.
• Present at the residency colloquium.
• Experience startup pace firsthand.

Required qualifications

• Currently pursuing or recently completed a graduate degree (MS or PhD, or equivalent research experience) in computer science, AI, electrical engineering, physics, or a related field.
• Cross-functional by temperament.
• Strong Python skills.
• Proficiency with modern ML frameworks.
• Familiarity with agentic systems, reinforcement learning, or automated design and optimization loops.
• Systems-level thinking.
• A rigorous, evidence-first mindset about self-improvement.
• Strong written and verbal communication skills.

Nice to have

• Publications are a strong plus
• PyTorch preferred
• Exposure to hardware-side tooling (SPICE, FPGA or ASIC flows, or EDA software)
• Prior experience writing up research (papers, theses, technical reports)
• Experience presenting technical work to a live audience

About the company

Normal is an applied AI company solving the hardest problems in AI and silicon. They build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world.