HFT Execution & Alpha Monetisation

HFT Execution and Monetisation

About DeepFin Research

DeepFin Research is a proprietary high-frequency trading (HFT) firm powered by cutting-edge Deep Learning (DL) and Deep Reinforcement Learning (DRL). We've brought on teammates from Nvidia, DeepMind, CitSec, Graviton, Tower, Jump, and others, and are aggressively working across cutting edge AI research and traditional quant research methods to monetise our AI generated signals across the global financial markets.

The Role

We are looking for exceptional high frequency trading researchers to work at the intersection of research, engineering, low-latency execution, creating alpha and monetising existing alpha across different markets, products, and asset classes.

Key Responsibilities

• Monetise core alpha through efficient execution strategies across futures and related products.
• Expand trading universes - identify and onboard new instruments within existing markets and work closely with BD to identify new opportunities and exchanges. 
• Develop and refine execution logic - optimise market access, routing, and order placement to minimise slippage and latency impact.
• Collaborate closely with researchers, developers, and infrastructure engineers to bring models from research to production.
• Design and test short-term signals and execution algorithms to preserve alpha and reduce transaction costs.
• Monitor live strategies, diagnose performance drift, and implement continual improvements.
• Conduct PnL attribution and microstructure analysis to measure and enhance monetisation efficiency.
• Stay ahead of exchange microstructure changes and proactively adapt strategies to evolving market dynamics and market impact dynamics.

Ideal Candidate Profile

• 5+ years of experience in HFT or ultra-low-latency trading, ideally within futures markets (options experience is a strong plus).
• Proven track record in execution alpha monetisation - not just signal generation - you’ve taken models from idea to production.
• Deep understanding of L3 data, market microstructure, order book dynamics, and short-horizon predictive models.
• Hands-on experience in strategy deployment and productionisation, including calibration, risk controls, and post-trade analytics.
• Strong quantitative and programming skills - Python and C++ preferred; familiarity with distributed and low-latency systems advantageous.
• Knowledge of cross-exchange arbitrage, market making, or execution cost optimisation a plus.
• Highly analytical, commercial mindset with the ability to operate autonomously in a fast-paced, research-driven environment