Our client is an established proprietary trading firm trading its own capital across global markets. No external investors, no clients, research goes straight into production, and performance is the only feedback loop that matters. We're partnering with them confidentially on a small number of senior ML hires.
The role
You'll join a central ML research team that works across trading desks and asset classes, designing models that directly improve trading performance. This is a hands-on research seat — you own ideas end to end, from hypothesis to live model.
What you'll do
- Design, prototype and implement ML models that improve trading performance across asset classes
- Research novel algorithmic approaches and test them against real market data
- Partner with traders and quantitative researchers to turn market intuition into data-driven features
- Own data acquisition, preprocessing and feature engineering for your research
- Work on low-latency predictive models where microseconds are a design constraint, not an afterthought
What they're looking for
- PhD or Master's in CS, Engineering, Math, Statistics or a related quantitative field
- 3+ years developing and deploying predictive models in low-latency environments
- Strong experience building your own novel architecture
- Strong Python; deep fluency in PyTorch (or JAX / TensorFlow)
- Genuine command of the theory behind modern ML, architectures, attention, optimization, not just API-level familiarity
- Publication record at ICML / ICLR / NeurIPS is a strong plus
Trading experience is not required. They hire from top research and engineering environments: big tech, national labs, leading academic groups, as often as from the industry.
Why it's worth a conversation
- Central research team with reach across the whole firm, your work isn't siloed to one desk
- Immediate, measurable feedback on every idea you ship
- Serious compute and serious data, with none of the product-roadmap drag
- Industry leading compensation