attimet
we predict stuff
AI Researcher / Quant
About the role
Why you should join us
- We’re building a research lab with a real-time feedback loop: the financial markets.
- We're working with structured and unstructured data at scale to build temporal AI systems that adapt, predict, and act.
- Our edge isn’t secret data or microwaves — it’s the speed at which we iterate and learn.
- You’ll lead ML/AI strategy at the intersection of research and live deployment.
- We’re starting in options - complex, under-modeled, and full of opportunity.
- Join a frontier team with over a decade of experience in quant trading. These aren’t logos from internships - we’ve started and led teams at Optiver, DRW, and Argo AI.
What you’ll do
- Lead development of predictive models, RL agents, and signal discovery workflows.
- Integrate alternative data, design experiments, and rapidly test hypotheses in sim + live trading. Measure your impact in market returns.
- Work side-by-side with the founders to test predictions in real markets and learn from every outcome - good and bad.
- Shape the research direction, modeling stack, and experimental culture from day one.
What we’re looking for
- Deep expertise in ML/AI - especially time-series, forecasting, representation learning.
- Strong coding background: Python, data pipelines, AWS/GCP infra.
- Experience deploying models in production: you care about what works, not just what looks good on paper.
- Clear thinker, fast builder, excited to work at the edge of research and execution
- Zero experience in financial markets is expected. Drive and curiosity matter.
You’ll be given the autonomy to do some of the best work for your life.
About attimet
We’re building a research lab that puts its ideas to the test in one of the most complex, information-rich environments in the world: the financial markets.
Much of trading still depends on hand-crafted signals and intuition. We’re approaching it differently - from first principles. We design systems that learn, adapt, and improve with data. Our infrastructure is built to accelerate research: fast iteration loops, real-time feedback, and direct connection between ideas and outcomes.
We’re starting with liquid markets like equities and options - high-dimensional, dynamic systems where traditional pipelines break down. Our goal isn’t just to model them better - it’s to build a platform for experimentation, where every result tightens the loop between theory and practice.
If you care about learning systems, clean abstractions, and applying research in the wild - we’re hiring.
