Elon Musk’s xAI is hunting for crypto market veterans to teach its machines how to “think” about money on blockchains — a hire that blends hands-on trading experience with AI training. The company has posted a remote role titled “Finance Expert — Crypto,” and multiple reports say it’s looking for people with deep, real-world market know-how. Candidates will be asked to translate complex events into simple explanations, annotate live examples, and create training materials the models can learn from. The job goes beyond advisory work: xAI wants experts who can break down liquidity shifts, trace on-chain flows, and explain how traders react under stress. Day-to-day work will include reviewing model outputs and flagging where the AI missed the point, producing audio or video walk-throughs, and preparing written notes and annotated datasets. Tasks will draw on market charts, on-chain evidence and plainspoken commentary so the models learn to weigh different signals correctly — e.g., distinguishing structural moves from short-term noise. Reports suggest pay could sit between roughly $45 and $100 per hour depending on experience and duties, a range that has already sparked online discussion. xAI is reportedly casting a wide net to find scarce expertise, and this hiring push aligns with broader moves inside Musk’s sphere: the company has recently struck a deal that observers say brings it closer to his space-focused ventures. Why it matters: combining compute, proprietary data and frontline market expertise could let AI models parse complex crypto signals and explain them in human terms — improving analysis for research or risk teams. That doesn’t mean the model will become a ready-made trading coach on demand, but it could be taught to surface and contextualize the patterns traders care about. Those brought on will likely spend much of their time sorting real trades, flagging outliers, and labeling examples so the AI learns when on-chain flows indicate a structural shift versus fleeting noise. For readers: this is a concrete step toward marrying on-chain analytics with large-model capabilities — potentially useful for market analysis, compliance and risk tools, while also raising questions about how such systems will be used. Featured image: Unsplash; chart: TradingView. Read more AI-generated news on: undefined/news

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