Machine Learning Engineer • Mid-Level

Who you are

You have a strong background in machine learning and systems engineering, with experience designing and implementing scalable solutions that tackle complex challenges. You understand the intricacies of fraud detection and are passionate about using technology to combat it. Your expertise in machine learning allows you to build models that are not only effective but also efficient and reliable. You thrive in a remote-first environment, demonstrating self-motivation and ownership in your work. You are comfortable collaborating with cross-functional teams and have a knack for communicating complex ideas clearly.

Desirable

Experience with Go is a plus, as you will be working on backend systems that support machine learning models. Familiarity with fraud prevention technologies and AML compliance will help you hit the ground running. You are eager to learn and adapt to new technologies and methodologies, contributing to a culture of continuous improvement.

What you'll do

As a Machine Learning Engineer at Sardine, you will design and implement systems that make fraud detection possible. You will work on data pipelines that ensure the smooth operation of machine learning models, optimizing them for performance and scalability. Your role will involve collaborating with data scientists and engineers to develop end-to-end solutions that address high-stakes challenges in fraud prevention. You will be responsible for ensuring that the models you build run reliably and efficiently, contributing to the overall success of the platform. You will also have the opportunity to innovate and propose new approaches to enhance the effectiveness of our fraud detection systems.

What we offer

Sardine offers a remote-first work culture that allows you to work from anywhere in the United States or Canada. We value performance over hours worked, providing flexibility to maintain a healthy work-life balance. You will join a fast-growing company with a team of world-class professionals dedicated to making a meaningful impact in the fight against fraud. We encourage you to apply even if your experience doesn't match every requirement, as we believe in the potential of diverse backgrounds and perspectives.