Engineering PhD

About the Role

Role: Engineering PhD Opportunity Snapshot Pay: $80–95/hour Duration: Short-term pilot — approximately 2–3 weeks Project kickoff: Ideally end of week( November 8th) Location: Fully remote You’ll need: PhD or PhD candidate in electrical, mechanical, chemical, industrial, or aerospace engineering Your tasks: Build technical problems from real engineering workflows and define what makes an answer correct This is a short pilot, roughly 2–3 weeks, focused on real engineering workflows: the problems you’d actually encounter in your research or practice, not textbook exercises. You’ll build those problems, provide the correct analysis, and define what separates a right answer from one that only looks right. How the selection process works • Apply and complete the screening questions • Complete the AI interview for this role — it’s how your expertise gets in front of the client • Profile review • Onboarding — our Talent Ops team will get you set up Start Timeline & Availability We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

Responsibilities & Tasks

• Design technical problems drawn from real engineering work in your field, with realistic constraints and supporting data.
• Provide the correct solution and walk through the reasoning that gets there.
• Define objective criteria for correctness, so another engineer reviewing the work would reach the same verdict.
• Review problems built by other contributors for technical accuracy and soundness of method.
• Flag problems that turn out to be ambiguous or ungradable rather than submitting them.

Qualifications & Requirements

• PhD, or PhD candidate, in electrical, mechanical, chemical, industrial, or aerospace engineering.
• Degree from a strong research institution is preferred.
• Hands-on research or practice experience — problems you worked on yourself, not ones you read about.
• Able to explain why an answer is correct clearly enough that another engineer could verify it.
• Publications or a record of technical contribution is a plus.
• AI or LLM evaluation experience is a plus, but not required.

Eligibility