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Careers at HFT Architecture

We build short-horizon price prediction and the trading system around it: the forecast, the rules that trade on it, the risk layer and the path from a market event to an order. The work is done one market and one horizon at a time, and what we measure we write up with its sample and its limits. Every role is fully remote, and you can work from anywhere in the world.

Open roles

  1. Remote, from anywhere · Middle+ to senior

    Quantitative Researcher

    Quantitative researcher, remote: short-horizon price prediction on order-book data, validated out of sample and written up with its limits. Apply on the page.

  2. Remote, from anywhere · Middle+ to senior

    Machine Learning Engineer

    Machine learning engineer, remote: a pipeline that turns order-book data into validated short-horizon price models, reproducible end to end. Apply on the page.

  3. Remote, from anywhere · Middle+ to senior

    Backend Developer

    Backend developer, remote: market-data connectors, order-book reconstruction and the measured path from a market event to an order. Apply on the page.

  4. Remote, from anywhere · Middle+ to senior

    Frontend Developer

    Frontend developer, remote: interfaces for watching a trading system and reading its research: dense charts, replay and control views. Apply on the page.

  5. Remote, from anywhere · Junior

    Junior Machine Learning Engineer

    Junior machine learning engineer, remote from anywhere: data, experiments and leak checks in a pipeline of price models on order-book data. Apply on the page.

How hiring works

  • You apply on the role's page. A link to your résumé, LinkedIn or GitHub and a few sentences about what you built. No file and no cover letter.
  • A technical conversation. About work you have done: what the system was, which part was yours, what you would do differently.
  • One practical task, close to the work the role does and small enough to finish in an evening.
  • A decision, with the reason.

The two research roles ask one question about an article we published. Read the article first. The answer is the part of the application we read most closely.