Formal Verification Research Scientist
VoltaiJob Title
Formal Verification Research Scientist
Role Summary
Develop formal verification methods to prove hardware design correctness using model checking, property verification, and equivalence analysis. Collaborate with RTL, verification, and ML research teams to build scalable hybrid formal engines for AI-generated hardware.
Prototype and evaluate research ideas on real RTL, automate assertion synthesis, and turn methods into practical verification systems.
Experience Level
Mid-level — 5+ years of relevant experience (research in formal methods, model checking, theorem proving, or program analysis).
Responsibilities
Primary responsibilities include research, prototyping, and collaboration to deliver formal verification solutions.
- Research and develop formal verification algorithms (model checking, theorem proving, equivalence checking).
- Define formal properties and automate assertion/property synthesis.
- Prototype and evaluate methods on real RTL designs and benchmarks.
- Collaborate with RTL, verification, and ML teams to integrate methods into production tools.
- Design hybrid formal engines that scale to AI-generated hardware.
- Perform abstraction refinement, property decomposition, and formal coverage analysis.
Requirements
Must-have technical experience and tools knowledge.
- 5+ years of experience in formal methods, theorem proving, model checking, or program analysis.
- Hands-on experience with formal verification tools such as JasperGold, VC Formal, or equivalents.
- Experience with assertion-based verification (SVA) and property decomposition.
- Experience in equivalence checking, abstraction refinement, and formal coverage metrics.
- Ability to prototype research ideas and evaluate them on RTL.
- Strong collaboration skills with RTL, verification, and ML teams.
Education Requirements
Not specified.
About the Company
Company: Voltai
Headquarters: Palo Alto, CA, United States
Voltai develops AI-driven world models and agents to design, evaluate, and optimize physical systems—focusing on hardware, electronics, and semiconductors to enable AI-led hardware co-design, performance modeling, and cross-domain optimization.
