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Voltai

AI world models for chip design & manufacturing

Research Engineer - Mid-Training

AI ResearchConfirmed live in the last 24 hours
Full-timePalo Alto, CA, USANo salary listedIn-person

About the Job

Requirements

  • Experience training large language models or foundation models on semiconductor design and verification corpora, such as RTL, netlists, PDKs, or simulation logs.
  • Experience modeling design scaling laws and optimizing compute budgets for chip-design-specific workloads.
  • Experience generating large-scale synthetic design data, such as RTL variants, testbenches, or verification traces.
  • Experience building evaluations that correlate with downstream design metrics, such as timing closure, power, area, or verification coverage.

Responsibilities

  • Train frontier models to become highly knowledgeable semiconductor design and verification experts for reinforcement learning and automated chip development.
  • Develop methods for generating and curating synthetic design data, performing model distillation, and enabling continual learning at scale.
  • Work with hardware engineers, reinforcement learning researchers, and verification specialists to create evaluations that guide design data quality and model improvement.
  • Collaborate with compute engineers to scale efficient training across thousands of GPUs and reinforcement learning environments.
  • Build high-performance tools to investigate how data and simulation shape model-driven design intelligence.

About the Company

Voltai

AI world models for chip design & manufacturing

Voltai builds AI models and agents that learn, plan, and experiment in the physical world, starting with semiconductor design and manufacturing. Its world models run virtual experiments, then validate results in real fabrication settings to build rich datasets across the hardware stack. What sets Voltai apart is a team of Stanford researchers, former chip-industry CTOs, and policy veterans working with major semiconductor, electronics, and automotive manufacturers. The goal is to speed hardware innovation through AI-driven simulation and validation.

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