Our client is a globally recognised name in High-Frequency Prop Trading and Market Making and known for consistent success and impressive profitability. With continued growth across the firm, they are now looking to expand their world-class Quant Development team by hiring a genuine Quant Engineer with some commercial exposure to coding in Rust.

(FYI: the base salary advertised does not include cash bonuses, paid bi-annually. Your total annual will vary but is typically 60-100% of your base salary)

THE ROLE:

The successful applicant will work within a small autonomous team that acts as a conduit between the low-level core development team and the front office quant researcher and traders across multiple trading platforms (Prop, Market Making & OTC Derivatives)

You will work closely with the hands-on Quant Dev Lead within a flat structure, enjoy significant autonomy and a particularly collaborative relationship with the front office where roles/responsibilities typically overlap. For context, it is not unusual for the Quant Dev team to design and deploy trading strategies directly, so this is a fantastic opportunity for a talent Quantitatively focused engineer to showcase their talents.

The role focuses on designing & implementing Quant Trading strategies as opposed to having more of a lower-level technical latency/performance emphasis so you will need to demonstrate a strong understanding of Systematic Quant/Algo Trading and have strong mathematical capabilities.

KEY RESPOSIBILITIES:

• Collaborating with Quant Traders & Researchers to design, implement, and test trading strategies and algorithms
• Automating the deployment and monitoring of trading strategies to ensure optimum effectiveness
• Creating tooling and infrastructure to support research and improve decision-making, such as data analytics and strategy optimization tools
• Architecting and maintaining high-performance trading systems using Rust

SKILLS / EXPERIENCE REQUIRED:

• Some demonstrable commercial experience coding in Rust
• Understanding of trading strategies such as arbitrage, market-making, or execution flow
• Solid grasp of algorithm design, data structures, and quantitative finance fundamentals including concepts like limit order books, price discovery, and microstructure dynamics
• Exposure to performance-critical systems: real-time data flows, shared memory communication, and techniques to minimize memory allocation and copying
• Degree in a technical discipline such as Computer Science, Engineering, Mathematics, or Physics (postgraduate qualification a plus)
• Prior experience in high-frequency trading or electronic markets is beneficial, but not mandatory

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