Machine Learning Quant Engineer

Michael Page (UK); City Of London; On-site; GBP 125,000 - 150,000; Full time

Job summary

A leading recruitment firm is seeking a Machine Learning Engineer to design and implement innovative ML models for financial applications. The role involves collaborating with quantitative analysts and requires advanced knowledge in machine learning techniques, specifically in financial contexts. This position offers a daily rate of up to £1200 and requires being in the office 4 days a week in Central London.

Benefits

Competitive daily rate

Exposure to cutting-edge ML projects

Temporary role in a global organization

Qualifications

• Demonstrates deep understanding of ML algorithms and has hands-on experience with deep learning architectures.
• Understands financial instruments, derivatives, and risk management principles.
• Expert in Python and familiar with ML frameworks.

Responsibilities

• Design and implement machine learning models for financial applications.
• Build scalable ML pipelines to process financial data efficiently.
• Collaborate with quantitative analysts to align ML models with pricing methodologies.

Skills

Advanced Machine Learning Expertise

Strong Financial Domain Knowledge

Technical Proficiency in Python

Data Engineering & Infrastructure Skills

Model Optimisation & Deployment Experience

Collaborative & Business-Focused

Innovative & Analytical Mindset

Tools

PyTorch

TensorFlow

JAX

scikit-learn

XGBoost

LightGBM

Spark

Dask

SQL

NoSQL

AWS

GCP

Azure

Job description

• Up to £1200 per day. Based in Central London
• Machine Learning Engineer with Quant experience.

About Our Client

The hiring organisation is a large entity within the financial services industry.

Job Description

• Design and implement machine learning models for financial applications, with a focus on derivatives pricing, risk analytics, and market forecasting.
• Build scalable ML pipelines to process large volumes of financial data efficiently.
• Develop deep learning architectures for time series prediction, anomaly detection, and pattern recognition in market data.
• Optimise model performance using techniques such as hyper-parameter tuning, ensemble methods, and neural architecture search.
• Collaborate with quantitative analysts to align ML models with pricing methodologies and identify opportunities for innovation.
• Support the deployment of ML solutions into production systems for real-time risk management and pricing automation.

The Successful Applicant

• Advanced Machine Learning Expertise - Demonstrates deep understanding of ML algorithms (supervised, unsupervised, reinforcement learning) and has hands-on experience with deep learning architectures like RNNs, LSTMs, and Transformers.
• Strong Financial Domain Knowledge - Understands financial instruments, derivatives, and risk management principles, with experience applying ML in trading, pricing, or risk analytics contexts.
• Technical Proficiency - Expert in Python and familiar with ML frameworks such as PyTorch, TensorFlow, and JAX. Skilled in using tools like scikit-learn, XGBoost, and LightGBM.
• Data Engineering & Infrastructure Skills - Comfortable working with big data technologies (Spark, Dask), SQL/NoSQL databases, and cloud platforms (AWS, GCP, Azure). Able to build scalable ML pipelines for large-scale financial data.
• Model Optimisation & Deployment Experience - Proven track record of deploying ML models at scale, with experience in hyper-parameter tuning, ensemble methods, and neural architecture search.
• Collaborative & Business-Focused - Works effectively with quants and stakeholders to translate financial requirements into ML solutions. Communicates insights clearly and aligns models with strategic business goals.
• Innovative & Analytical Mindset - Capable of developing data-driven approaches that complement traditional quantitative models and drive measurable impact in pricing and risk analytics.

What\'s on Offer

• A competitive daily rate up to £1200 per day (inside IR35), depending on experience.
• The opportunity to work on cutting-edge machine learning projects in the financial services industry.
• A temporary role offering valuable exposure to a global organisation in London.
• BASED 4 DAYS PER WEEK IN THE OFFICE (Central London)