# Machine Learning Engineer at Sardine

_Remote · Full-time · Listed 2025-09-09 · Source: RemoteDevWork_

- Location: North America
- Pay (as listed): USD 175,000 - 220,000
- Pay (est. USD): $175,000 - $220,000

## Apply

Original listing: https://jobs.ashbyhq.com/sardine/2c8f0342-b8af-4cc2-85cd-67bc48275568/application
On RemoteDevWork: https://remotedevwork.com/jobs/9937/machine-learning-engineer

## 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 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.
- 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. Just a couple of things to keep in mind: pay is based on where you're located, and you'll need to keep a home base in the country you're hired in. So while we love the "coffee shop today, mountains tomorrow" life, this isn't a passport-optional, work-from-anywhere-on-Earth kind of remote - think flexible *within* your country, not borderless.

**Location:**
- Remote - United States or Canada

**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)*.*