Machine Learning Quant Engineer - Investment Banking

Harvey Nash; City Of London; On-site; GBP 85,000 - 120,000; Full time

Job summary

A leading investment bank in the City of London is seeking a Senior Quant Machine Learning Engineer to design and deploy ML-driven models. This high-impact role involves collaboration with traders and researchers, requiring over 7 years of relevant experience and expertise in Python. Ideal candidates will have a strong quantitative background and the ability to work in high-frequency environments.

Qualifications

• 7+ years of experience in a quant/ML engineering or research role within a financial institution.
• Advanced degree in a relevant discipline.
• Expert-level programming skills in Python and strong understanding of software engineering best practices.

Responsibilities

• Design, build, and deploy state-of-the-art ML models for various financial applications.
• Mentor junior quants and engineers.
• Collaborate closely with cross-functional teams.

Skills

Machine Learning

Python

Quantitative Modeling

Data Pipeline Architecture

Deep Learning

Time-series Forecasting

Education

PhD or Master's in Computer Science, Mathematics, Physics, Engineering

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

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