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Machine Learning Quant Engineer – Investment banking

Harvey Nash

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Harvey Nash
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Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London. **Inside IR35, 4 days a week on site** The role: To lead the design and deployment of ML-driven models across our trading and investment platforms. This is a high-impact, front-office role offering direct collaboration with traders, quant researchers, and technologists at the forefront of financial innovation.

Your Role Design, build, and deploy state-of-the-art ML models for alpha generation, portfolio construction, pricing, and risk management Lead ML research initiatives and contribute to long-term modeling strategy across asset classes Architect robust data pipelines and scalable model infrastructure for production deployment Mentor junior quants and engineers; contribute to knowledge-sharing and model governance processes Stay current with cutting-edge ML research (e.g., deep learning, generative models, reinforcement learning) and assess applicability to financial markets Collaborate closely with cross-functional teams, including traders, data engineers, and software developers What We’re Looking For Required: 7+ years of experience in a quant/ML engineering or research role within a financial institution, hedge fund, or tech firm Advanced degree (PhD or Master’s) in Computer Science, Mathematics, Physics, Engineering, or related discipline Strong expertise in modern ML techniques: time-series forecasting, deep learning, ensemble methods, NLP, or RL Expert-level programming skills in Python and strong understanding of software engineering best practices Experience deploying ML models to production in real-time or high-frequency environments Deep understanding of financial markets and quantitative modeling Preferred: Experience in front-office roles or collaboration with trading desks Familiarity with financial instruments across asset classes (equities, FX, fixed income, derivatives) Experience with distributed computing frameworks (e.g., Spark, Dask) and cloud-native ML pipelines Exposure to LLMs, graph learning, or other advanced AI methods Strong publication record or open-source contributions in ML or quantitative finance Please apply within for further details or call on (phone number removed) Alex Reeder Harvey Nash Finance & Banking EWJD2

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