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Engineering & Software Domain Expert

$105
per hour
Full-time Hybrid Last verified 21 Jul 2026
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About the Role

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models. We are hiring a senior engineering and software domain expert to work directly with a leading AI lab's research and program management teams, improving how frontier AI models reason about real engineering and software development work. Your engineering expertise is the substance of this role. You will review the quality of engineering knowledge work tasks, write the instruction specs and golden solutions that define what "correct" looks like, and build the benchmarks that show whether the model is genuinely improving. We are looking for a practicing specialist rather than a generalist.

What You'll Do

  • Data QA and reviews: Vet the quality of engineering knowledge work tasks and model outputs, spotting missing behaviors, thin reasoning, code that runs but is subtly wrong, unhandled edge cases, and answers that read well but would not survive a real code review.
  • Instruction specs and golden datasets: Write high-quality instruction specs, produce golden solutions to engineering problems, and define new engineering tasks that reflect how the work is actually done in practice.
  • Benchmarks and domain depth: Design challenging engineering tasks and evaluation sets, and help build engineering-specific skills and tools together with the research team.
  • Calibration: Work with client researchers and specialists in adjacent fields to keep standards consistent, translating tacit engineering judgment into explicit, teachable criteria.

You're a Good Fit If You

  • Education: Bachelor's degree or higher in computer science, software engineering, or a closely related engineering discipline. An MS or PhD is strongly preferred.
  • Experience: 4+ years of substantive professional engineering practice, building and shipping production software or engineered systems at a reputable organization. Internships and academic coursework alone do not count.
  • Domain depth: Genuine specialization in at least one area, for example distributed systems and backend infrastructure, security and cryptography, embedded and firmware, machine learning systems, developer tooling and platform engineering, or quality and test engineering.
  • Seniority: Clear progression to a senior level, for example Senior, Staff, Principal, Architect, or Engineering Lead, with real ownership of systems and design decisions.
  • Technical evidence: A visible record of engineering output such as shipped systems, granted patents, open source contributions, or published technical work. Preferred.
  • AI fluency: Hands-on working use of large language models in your professional work, and the judgment to tell a well-reasoned answer from a plausible-sounding wrong one.
  • Availability: Able to commit reliably to 40 hours per week for an initial engagement of 6 months.
  • Location: Living in the Bay Area, California, and able to work on-site with the client's team multiple days each week, when required. Candidates not currently based in the Bay Area must be willing to relocate there at their own cost. Relocation assistance is not provided.

Role Highlights

Pay
$65-$105/h
Contract
Full-time
Location
Hybrid
Category
Coding
Posted
2 months ago
Job ID
WE-7870

Pay & Payout

Independent contractor engagement. Apply via the link below - Mercor handles onboarding and pays weekly via Stripe or Wise.

Common Questions

Mercor has a reliability rating of very reliable based on the listings we track, with an onboarding time of 1-3 weeks (interview + assessment + trial). See our full Mercor review for the details behind that rating.

Applying takes you to Mercor's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.

$65-$105/h - Independent contractor engagement. Apply via the link below - Mercor handles onboarding and pays weekly via Stripe or Wise.

Data QA and reviews: Vet the quality of engineering knowledge work tasks and model outputs, spotting missing behaviors, thin reasoning, code that runs but is subtly wrong, unhandled edge cases, and answers that read well but would not survive a real code review. Instruction specs and golden datasets: Write high-quality instruction specs, produce golden solutions to engineering problems, and define new engineering tasks that reflect how the work is actually done in practice. Benchmarks and domain depth: Design challenging engineering tasks and evaluation sets, and help build engineering-specific skills and tools together with the research team.

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