Machine Learning Quant Engineer - Investment Banking/ XVA

Harvey Nash; City Of London; On-site; GBP 80,000 - 120,000; Full time

Job summary

A leading investment bank is seeking a Senior Quant Machine Learning Engineer in London to design and deploy ML-driven models for trading platforms. You will collaborate with traders and technologists, contributing to financial innovations. The ideal candidate has over 7 years of experience, a relevant advanced degree, and expertise in ML techniques such as deep learning and time-series forecasting. Competitive salary and on-site work expected.

Qualifications

• 7+ years of experience in a quant/ML engineering role within finance.
• Advanced programming skills in Python.
• Experience deploying ML models in production environments.

Responsibilities

• Design, build, and deploy ML models for trading platforms.
• Lead ML research and model architecture.
• Mentor junior quants and engineers.

Skills

Quantitative modeling

Machine Learning

Deep Learning

Python programming

Time-series forecasting

Education

PhD or Master's in Computer Science or related field

Tools

Spark

Dask

Job description

Overview

Senior Quant Machine Learning Engineer sought by leading investment bank based in the city of London. Inside IR35, 4 days a week on site.

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