At a Glance
- Tasks: Design systems for fraud detection and optimise data pipelines in a hybrid remote role.
- Company: Join Sardine, a leader in fighting financial crime with a remote-first culture.
- Benefits: Generous compensation, flexible time off, health insurance, and home office setup stipend.
- Other info: Work in a dynamic environment with opportunities for growth and innovation.
- Why this job: Make a real impact in fraud detection using cutting-edge machine learning technologies.
- Qualifications: Experience in applied ML, strong SQL skills, and a degree in Computer Science or related field.
The predicted salary is between 63000 - 77000 £ per year.
Sardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine’s platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture.
We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.
As a Machine Learning Engineer, you’ll do more than build models - you’ll design the systems that make fraud detection possible. You’ll work across modeling, data pipelines, and backend systems (Go) to ensure ML models run reliably, efficiently, and at scale. This is a chance to combine applied ML with large-scale systems engineering, owning end-to-end solutions that tackle high-stakes, ever-evolving challenges.
- 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.
- Champion best practices in testing, documentation, and observability.
- 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.
Generous compensation in cash and equity, 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), and a one-time stipend to set up a home office — desk, chair, screen, etc.
Machine Learning Engineer - Hybrid Remote employer: Sardine
Sardine is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the fight against fraud. As a Remote Integration Engineer, you'll benefit from flexible working arrangements, continuous professional development opportunities, and the chance to make a meaningful impact in a rapidly evolving industry. Join us in our mission to protect businesses and consumers alike, while enjoying the unique advantages of working with a global leader in fraud prevention.
