Machine Learning Engineer (Fintech)

TL;DR

Machine Learning Engineer (Fintech): Designing and deploying scalable fraud detection systems with an accent on real-time data processing and model reliability. Focus on building end-to-end ML pipelines, integrating models with backend services in Go, and ensuring high performance in a high-stakes financial environment.

Location: Must be based in the UK, Germany, Ireland, Spain, Poland, Bulgaria, or Lithuania

Salary: £110k–£145k (UK) or €85k–€140k (Europe)

Company

hirify.global is a leading agentic risk platform that unifies data to prevent fraud and financial crime in real time for global enterprises.

What you will do

• Build and optimize data pipelines and backend services to process device and behavioral data in real time.
• Develop and deploy ML models for fraud detection, ensuring reliability and efficiency in production.
• Transform raw data into production-ready features for fraud detection systems.
• Collaborate with platform and backend engineers to integrate models seamlessly.
• Maintain high standards of security, privacy, and compliance.
• Champion best practices in testing, documentation, and observability.

Requirements

• Must be based in the UK, Germany, Ireland, Spain, Poland, Bulgaria, or Lithuania.
• Hands-on experience with applied ML using large datasets (PyTorch, Scikit-learn).
• Strong SQL skills and familiarity with relational and non-relational databases.
• Experience with end-to-end ML systems including feature pipelines, deployment, and monitoring.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
• Excellent communication skills in English.

Nice to have

• Domain knowledge in fraud, risk, or cybersecurity.
• Background in Software Engineering.
• Familiarity with CI/CD, Docker, Kubernetes, and modern devops frameworks.
• Understanding of modern browser APIs and high-entropy data collection.
• Familiarity with leveraging frontier LLMs for automation.

Culture & Benefits

• Remote-first culture with a globally distributed team.
• Generous compensation package including cash and equity.
• Flexible paid time off and year-end break.
• Comprehensive health, dental, and vision insurance.
• Stipends for home office setup, monthly meals, social meet-ups, and annual learning.