Y Combinator-backed attimet is hiring a founding researcher/quant to lead AI strategy at their new research lab focused on financial markets. The San Francisco-based startup, founded in 2024, is building temporal AI systems that adapt, predict, and act in real-time trading environments, starting with options markets.
What you should know: attimet is taking a first-principles approach to trading by designing systems that learn and adapt with data, rather than relying on traditional hand-crafted signals and intuition.
- The company offers $100K-$150K salary plus 0.25%-1.00% equity for this full-time position requiring 3+ years of experience.
- The role involves leading development of predictive models, reinforcement learning agents, and signal discovery workflows while working directly with founders to test predictions in live markets.
- Zero financial markets experience is expected—the company prioritizes drive and curiosity over domain expertise.
The big picture: attimet represents a new wave of AI-first trading firms that leverage machine learning to navigate complex, high-dimensional financial systems where traditional approaches break down.
- The founders bring over a decade of experience from established quantitative trading firms including Optiver, DRW, and Argo AI.
- Their infrastructure is designed for rapid iteration with real-time feedback loops connecting research directly to market outcomes.
What they’re looking for: The ideal candidate combines deep machine learning and AI expertise with strong production deployment experience.
- Technical requirements include expertise in time-series forecasting, representation learning, Python, data pipelines, and AWS/GCP infrastructure.
- The company emphasizes practical results over academic achievements, seeking candidates who “care about what works, not just what looks good on paper.”
- The role offers significant autonomy to shape research direction, modeling stack, and experimental culture from day one.
Why this matters: The position represents an opportunity to apply cutting-edge AI research in one of the world’s most information-rich and challenging environments, where success is measured in direct market returns rather than theoretical metrics.
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