About the Company

I am working with a high-frequency trading firm based in Zurich — one of the fastest-growing systematic trading operations in the world. In a short space of time they scaled from zero to $250m+ AUM across crypto and equities. They are a significant participant on major exchanges, trading billions of dollars per month in notional volume. Alongside their trading operation, they run an in-house AI/ML research lab — a rare combination of cutting-edge research capability and the capital to deploy it directly into live markets. They hire methodically, targeting a team of around 10. Every person must have a strong, positive impact. The team you join will be among the most capable you have ever worked with. Founder-led. Real capital. Real systems. Real problems.

About the Role

The successful candidate will sit at the intersection of ML research and high-performance trading systems. This is not a role where you fine-tune models on toy datasets. You will work on genuinely hard problems: extracting signal from noisy, non-stationary financial data; applying cutting-edge architectures to alpha generation; building systems that are both intellectually rigorous and production-grade. You will have real ownership over your research agenda — and you will see your work deployed with live capital behind it.

Responsibilities

• ML-driven alpha research: Design and develop ML models for signal generation across crypto and equities, applying deep learning, transformer architectures, and advanced inference techniques to financial time series.
• Next-generation trading systems: Contribute to the architecture and optimisation of the ML trading engine, working at the boundary of research and engineering to ensure models are production-ready and performant.
• Novel AI research directions: Explore cutting-edge areas such as test-time computation, active inference, and System 2 reasoning as applied to trading and market modelling.
• Research rigour at scale: Develop frameworks for robust backtesting, model validation, and systematic research — maintaining the highest standards as the team and strategy library grows.

Qualifications

• Deep expertise in machine learning and deep learning — strong theoretical foundations and hands-on implementation experience.
• Fluency with large language models and transformer architectures — not just how to use them, but how they work.
• Exposure to advanced AI concepts: test-time computation, active inference, System 2 reasoning, or related areas.
• Familiarity with the ARC challenge is a significant plus — it signals the kind of rigorous, first-principles thinking they value.
• Strong engineering skills: clean, efficient code and a care for production quality, not just research prototypes.
• Intellectual curiosity that borders on obsession — you follow the field closely, form your own views, and pursue ideas with conviction.
• Comfortable in a small, high-ownership environment where you set your own direction and are accountable for outcomes.

Location

Based in Zurich. The firm welcomes applications from candidates in Switzerland or the EU/EFTA, and will support relocation — candidates should be able to relocate to Zurich within six months of joining.