NMLS licensed mortgage loan officers to build the origination scenarios frontier AI labs use to test model judgment. AfterQuery builds the expert evaluation data that frontier AI labs use to measure and improve their models. We're hiring NMLS licensed mortgage loan officers as contractors to author and grade the origination scenarios those evaluations run on. What you'll actually do Author realistic mortgage origination scenarios, from prequalification and program selection through underwriting and closing Write reference answers with the guideline reasoning behind each lending decision Grade model output for accuracy under agency and regulatory guidelines Flag advice that reads plausible but violates lending regulations Who this is for Loan officers with an active NMLS license or registration Originators with at least 2 years of mortgage origination experience Practitioners with depth in loan programs, underwriting guidelines, and disclosure requirements Clear writers who can document the reasoning behind a lending decision Contract and pay $70 to $105/hr , paid weekly via Stripe. Your rate is set from your experience, not negotiated down after you start. Fully remote, fully async. No fixed hours. Minimum 10 hours per week, no maximum. Scale up or down week to week. No screen recording, no keystroke monitoring, no idle timers. Independent contractor. Ongoing project work rather than single task batches. How our hiring process works Apply at /apply/mortgage-loan-officer-expert. About five minutes. Resume plus a few structured questions. Resume review. Every application gets read against a published rubric and gets a decision. Written assessment. You may be asked to take a written assessment for further placement. Onboarding. Sign the contractor agreement, connect Stripe, and get platform access. Project match. You're matched to live work in your specialty, usually within a week of onboarding. About AfterQuery AfterQuery is an expert data lab. We build the evaluation and training data that frontier AI labs use to measure what their models can and can't do in real professional work. Our contributors are practicing professionals, not annotators, and the work is credited, reviewed, and paid at professional rates.
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