About The Company
We are a fast-growing startup at the intersection of quantum computing and financial services, applying cutting-edge technology and innovative solutions to solve complex business problems for our clients.
About The Company
We are a fast-growing startup at the intersection of quantum computing and financial services, applying cutting-edge technology and innovative solutions to solve complex business problems for our clients.
Our mission is to deliver real-world impact through high-quality product development, operational excellence, and strategic client engagement. We value collaboration, curiosity, and ownership, and are building a team that thrives in a fast-paced, high-growth environment.
About The Role
We run algorithmic trading strategies across FX, equities, commodities and crypto, built on quantum and quantum-inspired research. Our scientists generate signals and our engineers run the platform. You connect the path between them, from a promising idea, through backtest and validation, to trading.
You would own that path. Partly by building the machinery: the backtest harness, the validation gates, the route to deployment, so the research team ships without waiting on anyone. Partly by doing the work yourself: applying machine learning to strategy development where it earns its place, and being honest about where it does not.
Key Responsibilities
- Own the path from research idea to live strategy, and make it faster and more repeatable.
- Build and maintain the backtest, validation and deployment tooling the research team depends on.
- Apply machine learning to strategy development where it outperforms the classical approach, and say so plainly when it does not.
- Guard against look-ahead bias, overfitting, survivorship, and build those guards into the tooling.
- Work with the science team on turning their research into something deployable, and with engineering on making it run.
- Document and hand over, so the machinery outlives you.
Required Experience
- Three or more years applying quantitative or machine learning methods to financial market data.
- Strong, production-quality Python that other people can maintain.
- Direct experience taking a model or strategy from research into something running live.
- A clear understanding of how backtests mislead, and how to design against it.
- Comfort working across teams without formal authority over either.
Ideal Experience
- Built or maintained a backtesting or research platform that others relied on.
- Familiarity with FX, futures or crypto market structure.
- C++ or Rust alongside Python.
- CI/CD, automated testing and infrastructure-as-code habits.
- Early-stage or high-growth experience, where the tooling did not already exist.
By submitting this application, I agree that my personal data will be collected, processed, and retained by the company solely for the purposes of managing and assessing my candidacy.
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