Voltai

System Architect at Voltai (Palo Alto, CA)

Voltai· Palo Alto, CA·

Role details

Employment
Full-Time

Job description

About Voltai

Voltai is developing world models, and agents to learn, evaluate, plan, experiment, and interact with the physical world. We are starting out with understanding and building hardware; electronics systems and semiconductors where AI can design and create beyond human cognitive limits.

About the Team

Backed by Silicon Valley’s top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents.

About this Role

You will define the architecture for advanced compute and hardware systems — integrating AI co-design, performance modeling, and cross-domain optimization. You’ll translate system-level requirements into cohesive architectures that balance power, performance, and scalability, guiding implementation teams toward next-generation platforms.

You might thrive if you have 5+ years of experience in

  • SoC or system architecture and performance modeling
  • Hardware/software co-design and cross-layer optimization
  • Interface definition, memory hierarchy, and interconnect design
  • Leading architecture reviews and specification development

Why work at Voltai

  • Culture: Emphasizes high-agency, interdisciplinary work at the intersection of AI and physical engineering. The team includes Olympiad medalists and former CTOs – a “smartest in the room” environment.
  • Remote/hybrid policy: Fully remote (as indicated on Built In and LinkedIn). Employees work from the United States and Germany.
  • Notable perks: Opportunity to work on frontier AI problems with direct impact on the semiconductor industry; access to unrivaled industry partners and compute resources.
  • Engineering culture: Heavy focus on research engineering (CUDA, post-training, systems), with open roles for both software and hardware engineers. Emphasis on real-world validation and iterative experimentation.

Application questions