**About the Opportunity**
A leading AI research organization is evaluating how advanced AI systems perform in specialized engineering domains, and is seeking expert hardware engineers with deep, hands-on RTL experience in **SystemVerilog and/or Verilog**. You'll apply your expertise to assess complex, real-world technical scenarios — directly shaping how cutting-edge AI performs in hardware design. _Single-language specialists are strongly encouraged to apply._
**What You'll Do**
- Apply your RTL expertise to evaluate technical tasks against real-world professional standards
- Review intricate code-level situations and provide precise, structured written assessments
- Work inside containerized repositories (Docker), running and interpreting programmatic and CI-style checks to judge whether an engineering environment is sound
- Provide clear written rationales explaining your expert judgments
- Complete well-defined, time-bounded tasks with explicit evaluation criteria
**Who We're Looking For**
We value strong engineering fundamentals, fast ramp-up, and high ownership over single-language pedigree alone — but deep specialists are very welcome. The ideal candidate brings:
- **5+ years** of professional or research RTL experience in SystemVerilog or Verilog
- Hands-on depth in RTL design, testbench/UVM verification, FPGA or ASIC work, and EDA toolchains (Vivado, Quartus, Synopsys, Cadence)
- Comfort working in **Linux/Docker-based repo environments** and reading automated/CI checks — or the ability to ramp on these fast
- Ability to articulate not just _what_ code does but _why_ it's correct or idiomatic, clearly in writing
- _Welcomed:_ engineers from semiconductor, telecom, defense/aerospace, national-lab, or academic backgrounds; non-traditional digital footprints are fine — a GitHub profile is not required
**Why This Work Matters**
RTL design underpins the world's semiconductors yet remains among the least-represented domains in AI research. The expertise you bring is rare, and your assessments directly influence how AI systems learn to operate in it.
**Engagement Details**
- Compensation: **$110–190/hour**, based on depth and experience
- Expected commitment: **20–40 hrs/week**
- Task flow is variable — work tends to arrive in waves, and there can be a lag between task batches. We're looking for people who stay flexible, including availability on weekends when needed, and who take ownership of keeping the project moving forward
- No proprietary tooling required — tasks are completable without employer-provided systems