Machine Learning Quant Engineer - Investment banking/ XVA

Harvey Nash • TRAFFIC • London, Not Specified, United Kingdom • £1,000 - £1,200 / * • 10h ago

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 ForRequired:

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 Alex ReederHarvey Nash Finance & Banking

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