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Job Description & How to Apply Below
They’re now looking to add a Quant Developer who thrives in a fast-moving start-up environment and wants real ownership over mission-critical trading infrastructure. This is not a siloed role. You’ll sit close to the research, trading, and execution stack, helping to design, build, and scale systems that directly impact P& L from day one.
What You’ll Do
Build, maintain, and evolve production-grade trading systems that manage and execute orders across multiple MFT strategies and exchanges in equities, crypto, and futures Optimize performance, reliability, and latency across the execution stack, with a strong focus on robustness in live trading environments Partner closely with quant and machine learning researchers to continuously refine data pipelines, signals, and execution logic
Contribute broadly as a hands-on engineer —stepping in across software and quant-development workloads as needed in a demanding startup setting
What They’re Looking For
Strong experience building high-performance, production-quality code in a trading or similarly latency-sensitive environment Comfort working across multiple asset classes and exchanges , or the curiosity and ability to ramp up quickly A pragmatic, problem-solving mindset—someone who enjoys shipping, iterating, and improving real systems
The flexibility and ownership mentality required to succeed at an early-stage fund
Technical Requirements
Strong BSc, MSc or Ph D academic background in Machine Learning, Computer Science or Engineering
Advanced Python skills; experience with Py Torch, Tensor Flow, Num Py, pandas, scikit-learn
Nice to Have
C++ or other low-level language experience
Experience with distributed computing or large-scale data pipelines
Prior experience in systematic trading, prop trading or quant funds
Equities mid-frequency
Why Join?
Start-up culture with genuine roadmap to $1billion AUM
Equity on offer alongside excellent base plus bonus
Machine learning is core to the investment process, not an overlay
Exposure to multiple asset classes within a unified research framework
Opportunity to influence model design, data architecture and research standards
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