In this hourly, remote contractor role, you will work as a Finance & Accounting Subject Matter Expert (SME) to create realistic professional tasks, evaluate AI-generated financial work, and design detailed rubrics defining what a high-quality professional response should…
Remote AI Expert - Finance Jobs in United States 2026
157 remote jobs open to candidates in United States in AI Expert - Finance. Updated daily.
Role Title: Finance Specialist - Executive Presentation Review Role Type: Contractor Location: Remote (US, UK or CAN micro1 is engaging Finance Specialist to contribute to a customer's project focused on elevating the quality, impact, and clarity of financial presentations and…
Mercor is hiring experienced Securities, Commodities, and Financial Services Sales Agents to help evaluate and improve cutting-edge AI systems.
We're working with a leading foundational AI lab to find experienced financial analysts from top-tier banks, PE/HF firms, or corporate finance teams who can help train their latest language model on document creation tasks.
Models manage cash on paper and miss what keeps a company solvent: a liquidity forecast that ignores timing, an FX hedge that leaves the real exposure open, a funding plan that assumes the market is always there.
Models talk about markets like a textbook and trade like they've never been filled: a strategy that ignores the bid-ask, a hedge that's wrong by a Greek, position sizing with no respect for slippage or where the liquidity actually is.
Models love a founder's story and can't tell a real market from a rounded-up one: a TAM built by multiplying optimism, traction metrics that don't cohort, a moat that's really just a feature.
Models write an equity note that sounds like the sell side and falls apart under a covering analyst's read: an estimate that ignores guidance, a target price with no bridge from the model, a thesis that forgets the last three quarters actually happened.
Models give financial advice that sounds reassuring and quietly ignores the client: a tax-blind withdrawal plan, an allocation that forgets the time horizon, an estate suggestion that would fall apart in probate.
Models approve a borrower that any underwriter would flag: cash-flow coverage computed off the wrong line, covenants that don't bite, a rating that ignores where we are in the cycle. Someone has to find the default risk hiding in a clean-looking spread, and that someone is you.
Ask a model to build a forecast and it returns a clean-looking model whose drivers do not connect, whose assumptions defy the business, and whose variance bridge does not tie to actuals. The formatting is immaculate; the logic leaks.
Models build an LBO that returns a tidy IRR and skip the parts that make or break a deal: a debt schedule that ignores the covenants, an entry multiple with no exit story, diligence that takes management's projections at face value.
Models write a pitch deck's worth of confident deal analysis and miss what a deal team lives on: a comps set stuffed with the wrong peers, an accretion/dilution model that ignores the financing, a synergy number pulled from thin air.
Models can recommend a portfolio that reads well and quietly breaks every rule that matters: concentrated bets dressed as diversification, a Sharpe ratio computed on overlapping exposures, position sizing that ignores liquidity and drawdown.
Models handle textbook finance fine and fall apart on the real thing: mispriced risk, subtly wrong derivations, and models that ignore market microstructure.
Models can build a three-statement model that looks clean and still get the mechanics wrong: a balance sheet that doesn't balance, working capital that flows the wrong way, a circular reference silently zeroed out.
We're hiring finance experts to evaluate AI-generated outputs related to transaction finance. Our goal is to improve how artificial intelligence processes complex financial data and structures transaction-related information.
Practitioner finance experts to write and review real world finance scenarios and grade how AI models handle them. AfterQuery works with leading AI labs to improve how their models handle real world finance.
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real macro analysis.
We are partnering with a biotech and pharma research team on expert human-evaluation work — creating and critiquing rubrics that analyze commercial drugs and drug-development programs.
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real financial analysis.
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real financial analysis.
As a Finance Domain Expert, you will collaborate with AI and engineering teams to improve the performance of financial AI models by defining workflows, creating evaluations, curating data, and providing domain-specific insights.
The research teams behind the best-known AI models come to Mercor for financial judgment they can't generate on their own. Your standards and expertise become the rubric that frontier AI is graded against.