About the Role

As a Machine Learning Engineer at Sardine, you will own the systems enabling real-time fraud detection. The data science team builds custom models for clients, while you build and run the deployment platform and low-latency serving path. Sardine scores millions of sessions in real time from hundreds of signals within a sub-250ms budget, shaping how features are computed, models are deployed, and degradation is detected.

Responsibilities

Construct and manage the model serving infrastructure, real-time inference, feature retrieval, and the associated latency budget.
Develop the deployment pipeline that enables data scientists to independently ship models, including support for clients hosting their own models.
Assume ownership of models in production, covering monitoring, drift detection, retraining, incident response, and on-call duties.
Create and enhance pipelines that convert raw device and behavioral signals into production-ready features.
Collaborate across Python and the Go backend to maintain fast inference within the request path.
Build models personally when appropriate, approximately 20% of the role, with the option to increase that proportion.
Advocate for testing, observability, security, and compliance within a regulated environment.

Nice to Have

Domain knowledge in fraud, risk, or cybersecurity.
Familiarity with CI/CD, Docker, Kubernetes, and modern DevOps frameworks.
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.

Work Arrangement

Remote - United States or Canada

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 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 family dinner, school plays, friends' gatherings, or doctor's appointments for an arbitrary schedule.
We're a remote-first team spread across time zones, so no office to report to. Work from wherever helps you do your best work. Pay is based on location, and you need a home base in the country you're hired in. This is flexible within your country, not borderless.

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.

Sardine is hiring a Machine Learning Engineer