Although many corporations envision an era in which generative artificial intelligence might entirely replace the responsibilities of a junior-level employee, the present reality falls considerably short of that ambition. At this stage—often referred to as AI’s “shadowing era”—the technology operates more as an attentive apprentice than as an autonomous worker. It figuratively sits beside human professionals, learning through observation and refinement, studying how experienced individuals make decisions, solve problems, and communicate nuanced information within complex workflows. This phase is essential, as machine learning systems must first absorb a vast amount of real human reasoning before they can begin to emulate it with accuracy and contextual understanding.
The process by which these systems evolve, commonly known as AI training, is both intricate and profoundly dependent on human judgment. To make a large language model’s responses more precise, relevant, and realistic, human evaluators are tasked with assessing the quality of its answers. They determine whether the AI interprets prompts correctly, articulates responses that align with professional reasoning, and avoids factual or contextual errors. In other words, the human role is to refine the AI’s cognitive edges, helping it progress from crude pattern recognition toward something more akin to analytical comprehension. The need for expert oversight becomes particularly pronounced when AI is applied to highly specialized or “wonky” professions—fields such as investment banking, wealth management, or private equity—where authentic examples of work and insider knowledge are incredibly scarce online. In these niches, human guidance becomes not merely useful but absolutely indispensable.
This reliance on human expertise has created a new market niche for AI training firms, whose demand for subject-matter specialists has grown sharply. According to a recent review conducted by Business Insider, companies like Mercor, Outlier (a subsidiary of Scale AI), and Elon Musk’s xAI are offering lucrative hourly wages to financial professionals who can lend their practical insights to training efforts. In fact, a survey of 18 job postings across eight organizations revealed that these firms are willing to pay impressive rates to workers who bring authentic industry experience from areas such as corporate finance, investment analysis, or portfolio management.
Among the opportunities listed, the most generous publicly advertised compensation reaches as high as $150 per hour. This figure appeared in a posting by Alignerrr, a company owned by Labelbox, which is seeking candidates with backgrounds in financial planning and wealth management—a field requiring intimate familiarity with client advisory, asset allocation, and long-term investment strategy. On the lower end of the pay spectrum, rates of around $15 per hour still surface, highlighting the breadth of different project scopes and expertise levels demanded by these firms. Meanwhile, xAI is offering compensation ranging from approximately $35 to $100 per hour for a variety of AI Tutor positions. These positions encompass professionals with sell-side expertise, such as those versed in investment banking and trading, as well as buy-side experts, including individuals with experience in private equity, venture capital, or hedge fund management. The company is even open to hiring those skilled in specialized disciplines like quantitative investing and portfolio optimization.
Another company, Micro1, posted a role titled “Finance Expert – AI Tutor.” Despite its general-sounding name, the listing reveals a search for someone with the elevated credentials of a former chief financial officer at a hedge fund. However, compensation details for this particular position remain undisclosed, leaving candidates to infer its potential competitiveness from comparable listings across the field. This naturally raises broader questions about who, exactly, is training artificial intelligence to understand the nuanced language and logic of global finance.
Interestingly, most of these training roles are designed as remote and part-time arrangements. This structure invites speculation: are these side jobs taken up by professionals currently employed at major financial institutions? Or are they perhaps attracting recently downsized bankers and analysts—those who found themselves with both financial need and highly transferrable expertise after corporate restructuring or layoffs? xAI, for its part, offers both physical and remote work options, with opportunities available in Palo Alto and flexibility across full- and part-time commitments. Outlier, according to a Scale AI spokesperson, provides comparable freedom, allowing contributors from diverse geographies and time zones to participate according to their own schedules. The same spokesperson mentioned an example of one contractor who maintains a full-time position in finance while moonlighting as a voice actor and AI data contributor, illustrating that these projects often complement professionals’ existing careers rather than replacing them.
Not all firms were eager to comment on their ongoing recruitment strategies, but promotional materials posted publicly provide some insight. In a recent LinkedIn video shared by Mercor, a man identified simply as Matt recounts his personal motivation for joining the platform. A first-year MBA student at the Wharton School, Matt explained that he initially joined Mercor as a short-term means to offset living expenses. Yet, he soon discovered that his prior background—as an investment banker at Bank of America and later an investor at the private equity firm Clayton Dubilier & Rice—allowed him to make far greater contributions than he had anticipated. In the video, he reflects that instead of merely helping himself financially, he wound up playing a small but meaningful part in constructing what he calls “the future of work.”
Mercor stands somewhat apart from the rest of the market by being the only company currently advertising fully full-time roles for these finance-oriented AI tutor positions. The salaries are substantial: listings indicate annual compensation ranging from about $90,000 to $200,000 for buy-side and sell-side tutor positions, with more specific investment banking expert roles offering between $90,000 and $120,000. Though these packages are competitive when compared to entry-level analyst compensation, they remain somewhat modest relative to the base salaries earned by associates at major financial firms. As of 2024, typical associate salaries in investment banking range from $170,000 to $230,000, according to industry data shared with Business Insider. Thus, although AI tutoring may not yet rival the financial rewards of Wall Street, it may offer an appealing alternative for individuals seeking flexibility, remote work opportunities, and relief from the punishing hours traditionally associated with high finance.
Indeed, for those weary of the relentless pace of major banks—the notorious late nights, weekend deals, and constant deadlines—these AI training roles may represent a form of professional reinvention. They blend financial expertise with participation in one of the most transformative technological shifts of the modern era. As human professionals lend their experience to teach machines the subtleties of global markets, valuation techniques, and ethical decision-making, they effectively shape the next generation of artificial decision-makers. For that reason, the experiment unfolding at the intersection of artificial intelligence and finance is not simply about automation or efficiency. It is, in a deeper sense, an exploration of how human judgment and computational intelligence can evolve toward a shared, collaborative future.
Sourse: https://www.businessinsider.com/how-much-ai-training-companies-paying-investment-bankers-wall-street-2025-11
