Machine Learning Engineer

🕒 June 20

🌐 United Kingdom, Germany, +5 more countries – Remote

🇬🇧 United Kingdom – Remote 🇩🇪 Germany – Remote 🇮🇪 Ireland – Remote 🇪🇸 Spain – Remote 🇵🇱 Poland – Remote 🇧🇬 Bulgaria – Remote 🇱🇹 Lithuania – Remote

💵 £110k - £145k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Sardine

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2020

🔒 Cybersecurity

📋 Compliance

💳 Fintech

Cybersecurity • Compliance • Fintech

Sardine is a cutting-edge platform focused on fraud prevention and compliance. The company offers a behavior-based system for fraud detection, identity verification, and transaction monitoring that helps leading banks, online retailers, and fintechs protect themselves from scams and financial crime. Sardine's technology integrates advanced behavioral biometrics and device intelligence to combat identity fraud, payment fraud, and account takeovers. The platform also streamlines compliance checks such as KYC (Know Your Customer) and AML (Anti-Money Laundering) transaction monitoring. Sardine's comprehensive solution empowers its clients to automate risk decisioning, identify high-risk users early, and manage fraud across the customer journey effectively.

📋 Description

• 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 they run reliably and efficiently in production. • Turn raw data into production-ready features that feed our 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

• Hands-on experience with applied ML using large datasets (PyTorch, Scikit-learn, etc.) • Strong SQL skills and familiarity with relational and non-relational databases. • Experience with end-to-end ML systems: feature pipelines, model deployment, monitoring, and iteration. • Excellent communication skills in English, both written and verbal. • Bachelor's or Master's in Computer Science, Engineering, or a related discipline. • Bonus Points • Domain knowledge in fraud, risk, or cybersecurity. • Background in Software Engineering • Familiarity with CI/CD, Docker, Kubernetes and the modern devops framework. • Understanding of modern browser APIs and high-entropy data collection techniques. • Familiarity with leveraging frontier LLMs for automation.

🏖️ Benefits

• Generous compensation in cash and equity • Early exercise for all options, including pre-vested • Work from anywhere: Remote-first Culture • Flexible paid time off and Year-end break • Health insurance, dental, and vision coverage for employees and dependents - *US and Canada specific* • 4% matching in 401k / RRSP - *US and Canada specific* • MacBook Pro delivered to your door • One-time stipend to set up a home office — desk, chair, screen, etc. • Monthly meal stipend • Monthly social meet-up stipend • Annual health and wellness stipend • Annual Learning stipend