Machine Learning Engineer

mthree; City Of London; On-site; GBP 65,000 - 85,000; Full time

Job summary

A leading technology firm in the City of London seeks a Machine Learning Engineer to design and implement advanced ML models focusing on financial applications such as pricing and risk analytics. Candidates should have expertise in neural networks, Python programming, and experience with big data technologies. This role offers a unique opportunity to work at the intersection of finance and machine learning. Ideal applicants will understand financial markets and possess strong programming skills.

Qualifications

• Deep understanding of various ML algorithms including supervised and unsupervised learning.
• Experience with neural network architectures such as RNNs, LSTMs, and Transformers.
• Strong understanding of financial markets and instruments.

Responsibilities

• Design and implement machine learning models for financial applications.
• Build scalable ML pipelines for large-scale financial data processing.
• Collaborate with quants on pricing model requirements.

Skills

Machine Learning algorithms

Neural networks

Python programming

Data processing

Risk management principles

Tools

PyTorch

TensorFlow

Spark

AWS

Job description

Machine Learning Engineer / ML Engineer

Machine Learning Development

• Design and implement machine learning models for financial applications, with a focus on pricing and risk analytics
• Build scalable ML pipelines for processing large-scale financial data
• Develop deep learning architectures for time series prediction, anomaly detection, and pattern recognition in market data
• Optimize model performance through advanced techniques including hyperparameter tuning, ensemble methods, and neural architecture search
• Collaborate with quants to understand pricing model requirements and identify ML opportunities
• Develop data-driven approaches to complement traditional quantitative finance models
• Support implementation of ML solutions for derivatives pricing and risk management

Core Technical Skills

Machine Learning Expertise

• Deep understanding of ML algorithms (supervised/unsupervised learning, reinforcement learning)
• Extensive experience with neural networks, including RNNs, LSTMs, Transformers
• Expertise in gradient boosting, random forests, and ensemble methods
• Experience with generative models (GANs, VAEs, Diffusion models)

Programming & Tools

• Expert-level Python programming
• Proficiency with ML frameworks (PyTorch, TensorFlow, JAX)
• Experience with scikit-learn, XGBoost, LightGBM
• Strong software engineering practices and clean code principles

Data & Computing

• Experience with big data technologies (Spark, Dask)
• SQL and NoSQL databases
• Cloud platforms (AWS, GCP, Azure)

Experience

• Track record of successfully deployed ML models at scale
• Experience with time series analysis and forecasting
• Experience applying ML in finance, trading, or risk management contexts
• Knowledge of stochastic processes and their applications

Financial Knowledge

• General understanding of financial markets and instruments
• Basic knowledge of derivatives and their risks
• Awareness of risk management principles