Staff Machine Learning Engineer, Radar

At Stripe, a Most Loved Workplace® certified employer in the Financial Services space, Economic infrastructure for the internet, powering ambitious businesses globally..

<h2><strong>Who we are</strong></h2>

<h3><strong>About the team</strong></h3>

<p>The <a href="https://Stripe.com/radar?utm_source=LinkedIn&utm_medium=paid-social&utm_campaign=emea_sold_enterprise_uk_en_mlp_tof_csuite_awareness&utm_content=radar_ungatedreport_all_image_learnmore_static&utm_placement=mlp">Radar ML</a> team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns 10+ real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates directly into dollar impact for Stripe and its users. </p>

<p>The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. Radar is growing fast, and the team is actively building new products like defenses against AI token theft, free trial abuse, and programmatic attacks.</p>

<h2><strong>What you'll do</strong></h2>

<p>In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch.</p>

<h3><strong>Responsibilities</strong></h3>

<ul>

<li>Design, build, train, evaluate, deploy, and own ML models in production that detect fraud across Stripe’s global payments network</li>

<li>Design and build large-scale ML systems that operate on diverse and large scale data</li>

<li>Experiment and iterate on ML models to achieve key business goals around data quality and accuracy</li>

<li>Develop pipelines and automated processes to train and evaluate models in offline and

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