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"top_startup_sources": [ "cbinsights_unicorn" ], "posted_at": "2026-02-25T09:07:44.993Z", "apply_url": "https://jobs.ashbyhq.com/airwallex/fd1ea805-4546-442a-9538-d66e213f3663", "apply_url_verified": false, "ats": "ashby", "url_last_checked_alive": null, "removed_at": null, "description_excerpt": "Data Platform Principal Architect SG - Singapore, Singapore About Airwallex Airwallex is the only unified payments and financial platform for global businesses. 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keeping critical minerals in circulation and driving the energy transition. 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San Francisco, San Francisco, California, United States About Airwallex Airwallex is the only unified payments and financial platform for global businesses. 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We're hiring a founding researcher to lead our simulation initiative, the model that lets AI systems predict what humans would think, want, and decide. Sequoia-backed, $100M raised, customers include Anthropic, Google, and Cursor. Background As AI gets better at building things, the bottleneck shifts to knowing what to build. We're the bridge between AI systems and what humans actually want. Today our customers are companies. Soon, AIs themselves will be our customers. Our platform runs AI-moderated video interviews at massive scale. We find the right people from a network of millions, our AI conducts open-ended conversations with thousands of them in parallel, and we surface what to build next. What used to take research teams weeks per study, we do in hours. Where it's going: every interview feeds a human preference model. We simulate human behavior at scale: how people react to new ideas, how they make decisions, how preferences shape markets, and how change ripples through society. We expose this as the Human API. An AI agent writes code, asks Listen whether users would actually want a feature, gets a grounded answer back, and iterates. Closed loop product development at AI speed. Every coding agent will eventually need this signal. Company highlights - Series B with $100M raised from Sequoia,", "matched_input": "ripple", "derivation_source": "candidate_result.raw_match_evidence", "candidate_evidence_id": "ev:gq_845036f1154de9ff6550:715d8cab394440e32819b6db126de4e5:description:ripple", "rerank_evidence_id": null, "taxonomy_alias_id": null, "oracle_verification_method": "candidate_evidence_exists", "counts_for_non_trivial_query": true, "truth_verified": true, "exact": true, "priority": 90, "mobile_priority": 1, "ui": { "icon": "Search", "tone": "match", "href": null } }, { "schema_version": "inv382.match_signal.v1", "signal_id": "sig.query.description_excerpt.7a2285152445b2b741", "query_id": "gq_845036f1154de9ff6550", "job_id": "715d8cab394440e32819b6db126de4e5", "signal_type": "query_match", "display_text": "Description: \"ripple\"", "tooltip": "Description contains \"ripple\" from your search.", "source_binding": "token_match", "source_field": "description_excerpt", "source_value": "Founding Research Scientist, Human Simulation San Francisco, CA, San Francisco, California, United States Founding Research Scientist, Human Simulation TL;DR: Listen is building a human-preference model that companies and AI agents query to predict what people think, want, and decide. We're hiring a founding researcher to lead our simulation initiative, the model that lets AI systems predict what humans would think, want, and decide. Sequoia-backed, $100M raised, customers include Anthropic, Google, and Cursor. Background As AI gets better at building things, the bottleneck shifts to knowing what to build. We're the bridge between AI systems and what humans actually want. Today our customers are companies. Soon, AIs themselves will be our customers. Our platform runs AI-moderated video interviews at massive scale. We find the right people from a network of millions, our AI conducts open-ended conversations with thousands of them in parallel, and we surface what to build next. What used to take research teams weeks per study, we do in hours. Where it's going: every interview feeds a human preference model. 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