Machine Learning Engineer - Financial AI

EC1 Partners; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

EC1 Partners is seeking a machine learning engineer to build models used across financial data, risk and automation use cases. You will work with engineers and product teams to deploy ML solutions into production, ensuring scalable, robust models in live environments.

Applicants should have ML engineering experience, Python and ML frameworks, and familiarity with deploying models to production in data-heavy financial services contexts. Cloud ML tooling exposure is highly valued.

Qualifications

• Experience in ML model development for finance or data-heavy domains.
• Proficient in Python and ML frameworks.
• Experience deploying ML models to production.
• Familiar with cloud ML tooling.
• Knowledge of financial services or data-heavy environments is helpful.

Responsibilities

• Develop and deploy ML models
• Work with structured financial datasets
• Collaborate with engineering teams
• Improve model performance and monitoring
• Support production ML pipelines

Skills

Machine learning engineering

Python programming

Model deployment

Financial services background

Cloud ML tooling familiarity

Tools

TensorFlow

PyTorch

AWS SageMaker

Job description

Role Overview

This role focuses on building machine learning models used across financial data, risk, and automation use cases. You'll work alongside engineers and product teams to deploy ML solutions into production.

Key Responsibilities

• Develop and deploy ML models

• Work with structured financial datasets

• Collaborate with engineering teams

• Improve model performance and monitoring

• Support production ML pipelines

Required Experience

• Machine learning engineering experience

• Python and ML frameworks

• Experience deploying models to production

• Financial services or data-heavy background

• Cloud ML tooling exposure

Nice to Have

• NLP or time-series modelling

• MLOps experience

• Risk or fraud use cases

Why Join

• Applied ML in production

• High-impact financial use cases

• Growing AI capability