HFT Quantitative Developer

DeepFin is a systematic proprietary trading firm combining deep learning, traditional quantitative research methods, and cutting-edge trading technology, to trade global markets. Founded by engineers and researchers, we build and deploy advanced trading systems that operate across global markets.

Our team is lean, highly technical, and impact-driven - every hire plays a direct role in shaping the firm’s technology, strategy, and performance. We value curiosity, precision, and collaboration, and we’re building an environment where exceptional people can do their best work at the intersection of AI and financial markets.

We are looking for a Quantitative Developer to sit at the intersection of research and engineering, focused on taking high-frequency and mid-frequency futures alpha and turning it into scalable, production-grade PnL across global exchanges. This role is core to our monetisation pipeline: you will work directly with researchers to translate models and signals into robust, ultra-low-latency execution systems, and with engineers to optimise performance, stability, and deployment across multiple matching engines.

Options experience is desirable, particularly around surface fitting and microstructure, but not essential. The primary focus is on HFT futures execution, L3 data integration, and productionising trading strategies.

This is a hands-on, high-impact role for someone who can bridge modelling, software engineering, and live trading environments.

Key Responsibilities

• Productionise research models into high-performance C++ systems used for live trading across multiple futures exchanges.

• Integrate and process L3/order-book data at scale, building and maintaining parsers, normalised book structures, and data pipelines.

• Develop and optimise execution logic, order placement strategies, queue-positioning logic, microstructure-aware order types, and latency-sensitive workflows.

• Collaborate closely with quant researchers to understand signals, model assumptions, and expected behaviours, ensuring seamless transition from prototypes into production code.

• Work with infra/engineering teams to deploy, monitor, and refine strategies in live environments; diagnose latency bottlenecks, instability, and performance drift.

• Build and maintain simulation/backtesting tools for microstructure-accurate evaluation of execution behaviour.

• Optional (desirable): support vol surface modelling, options execution logic, and cross-asset HFT monetisation.

Required Experience & Skills

• Must have HFT Experience. Marketmaking experience also desirable. 

• C++ and Python

• Experience working with L3 and order-book data, market-data adapters, and high-throughput feed handling.

• Experience productionising HFT or mid-frequency futures strategies in live environments.

• Understanding of market microstructure: queue dynamics, adverse selection, order types, latency paths, tick-rule details.

• Ability to operate across both research and engineering disciplines: reading model code, understanding signals, and implementing robust production systems.

Desirable Experience

• Options trading infrastructure.

• FPGA familiarity.

If you’re passionate about applying advanced technology to real-world markets and want to work alongside a focused, high-performing team, we’d love to hear from you. DeepFin offers a collaborative, research-driven environment where ideas move quickly from concept to execution and where every contribution has visible impact.

Join us in building the next generation of deep-learning-driven trading systems - shaping the future of finance through innovation, rigour, and technology.