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HFT Quantitative Research and Trading

Bengaluru; Jersey; London; New York💼 Full-time🗓 2026-05-31 → 2026-07-31

Core

Monetizing deep-learning alpha through efficient execution strategies across futures and related products.

Role type

Senior HFT Quantitative Researcher and Trader

Builds

Low-latency execution systems and trading strategies for global futures markets

Domain

Financial markets (HFT/Futures) + Machine Learning

Deliverable

production ML models

Required skills

HFT execution strategy design, market microstructure analysis, order book dynamics, Python, C++, distributed systems, risk controls, post-trade analytics

Preferred skills

Options trading experience, cross-exchange arbitrage, market making, execution cost optimization

Technologies

Python, C++, L3 data, low-latency systems

Responsibilities

Monetize core alpha via efficient execution strategies, expand trading universes by onboarding new instruments, develop and refine execution logic to minimize slippage, collaborate to bring models from research to production, design and test short-term signals and execution algorithms, monitor live strategies and implement improvements, conduct PnL attribution and microstructure analysis

Seniority

Senior, hands-on IC

Rewrite
## HFT Quantitative Research and Trading ### The Role We are looking for exceptional HFT Quantitative Researchers and Traders to work at the intersection of research, engineering, low-latency execution, creating alpha and monetising our deep-learning alpha across a broad spectrum of 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 ### Benefits 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.
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