Remote Expert Hardware​/RTL Engineer – SystemVerilog​/Verilog - AI Trainer

Overview

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 System Verilog 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.

• 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

• 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 System Verilog or Verilog
• Hands-on depth in RTL design, testbench / UVM verification, FPGA or ASIC work, and EDA tool chains (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 Git Hub profile is not required

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.

• 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