Machine Learning Engineer

Job description

**Who we are:** 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. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products. **Our culture:** - We have hubs in the Bay Area, NYC, Austin, Toronto, and São Paulo. However, we maintain a remote-first work culture. #WorkFromAnywhere - We hire talented, self-motivated individuals with extreme ownership and high growth orientation. - 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. **Location:** - Remote - United States or Canada - From Home / Beach / Mountain / Cafe / Anywhere! - We are a remote-first company with a globally distributed team. You can find your productive zone and work from there. **About the role:** As a Machine Learning Engineer at Sardine, you'll own the systems that make real-time fraud detection possible. Our data science team builds custom models for our clients, you build and run the platform they deploy onto, and the low-latency serving path those models score on. Sardine scores millions of sessions in real time from hundreds of device and behavioural signals, inside a sub-250ms budget. That constraint shapes everything: how features are computed and served, how models are deployed and rolled back, how quickly you know when something has degraded. You'll be the person who figures out why a model broke. **What you'll be doing:** - Build and own the model serving infrastructure, real-time inference, feature retrieval, and the latency budget that governs both - Build the deployment path our data scientists use to ship models themselves, including bring-your-own-model support for clients hosting their own - Own models in production: monitoring, drift detection, retraining, incident response, and the on-call rotation - Build and optimise the pipelines that turn raw device and behavioural signals into production-ready features - Work across Python and our Go backend to keep inference fast inside the request path - Build models yourself where it makes sense, roughly 20% of the role, and more if you want it - Champion testing, observability, security and compliance in a regulated environment **What you'll need** - Experience building, not just using, model serving infrastructure. - Production ownership of ML systems: you've been paged when something broke, you found out why, and you changed something so it didn't happen again. - Strong Python, and solid software engineering fundamentals, testing, code review, CI/CD, the discipline that makes a platform other people can rely on. - Comfort with Kubernetes, containers and a major cloud (we're mostly GCP), plus infrastructure-as-code. - Enough understanding of models to debug them. You don't need to have trained one recently, but when precision drops you should know the difference between a data problem, a feature pipeline problem, and a model problem - Experience building tooling other engineers or data scientists actually use, and the judgement to know what should be self-serve and what shouldn't. **Bonus Points** - Domain knowledge in fraud, risk, or cybersecurity. - 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 we offer:** - 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 Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you. _To learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our_ [_Applicant and Worker Privacy Notice_](https://www.sardine.ai/applicant-and-worker-privacy-notice)_._ Compensation Range: $175K - $220K