Machine Learning Engineer, Radar

Seattle, South San Francisco
8217 Risk Engineering

About the Role

At Stripe in the Financial Services space, Economic infrastructure for the internet, powering ambitious businesses globally..

<h1><strong>Machine Learning Engineer - Radar</strong></h1>

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

<h3><strong>About Stripe</strong></h3>

<p>Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.</p>

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

<p>The Radar ML team builds the machine learning systems that power Stripe’s Radar fraud and abuse product suite. Our models make real-time decisions across a significant share of internet commerce - helping businesses stop fraud, increase authorization, and grow safely. By turning economy-scale datasets into compelling ML products, the team directly improves customer outcomes and drives meaningful revenue for Stripe.</p>

<p>The team is growing, and expanding into multiple new areas. We are building abuse protections across the full customer life-cycle, adaptive and customizable fraud systems for enterprises, and risk intelligence for 50+ global payment methods. </p>

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

<p>You will own major ML systems and initiatives from problem definition to production. You'll find where ML can make the biggest difference, design the approach, build and ship models and the systems around them, and keep improving them as data, users, and attackers change.</p>

<p>Your work may include protecting businesses from abuse across the customer lifecycle, building adaptive and customizable fraud system

Want to learn more about what it's like to work at Stripe? View our full profile.

What It's Like to Work at Stripe

What It's Like to Work Here

Lightbulb Problem-Solving Excellence
Globe Global Perspective
Users Customer Obsession
Zap Ownership Mentality
Target Long-term Thinking

Frequently Asked Questions About Working at Stripe

Common questions candidates ask about this role and Stripe's workplace

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes.

Please review the specific job listing or contact Stripe's recruiting team for details on remote or hybrid work options for this role.

Salary information may vary by role and location. Please check the specific job listing or discuss compensation during the interview process.

Stripe is an established organization in its industry. The company focuses on maintaining a supportive workplace culture for all employees.

Key benefit categories include: Health & Wellness, Financial & Lifestyle, Learning & Development, Work Environment. You can view more details on their CertCheck profile.

The day-to-day environment is guided by core values such as Problem-Solving Excellence and Global Perspective and Customer Obsession.

The company has committed to inclusive practices including: Invest in Growth and Development and Foster Psychological Safety and Inclusion.

Stripe has a supportive and collaborative culture, recognized as a loved place to work by its team members.

Stripe currently has 719 open positions. They are hiring across departments like 8611 Security Analytics, 1654 Account Executives (AI), 1653 Startups - Account Executives (NA). You can view all current openings at certcheck.mostlovedworkplace.com/companies/stripe/jobs.

The interview process typically involves an initial recruiter screen followed by team interviews. Please contact Stripe's recruiting team for specific details on this role's process.

Apply for Machine Learning Engineer, Radar

Submit your application directly to the Stripe team. Let them know why you'd be a strong addition to their team.

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