Machine Learning Engineer

100% Remote (USA)

$140,000 - $175,000 Base + Annual Bonus + Equity

We're partnered with a rapidly growing technology company that is solving complex fraud and risk challenges at massive scale. Their machine learning team sits at the core of the business, building production models that directly influence millions of real-time decisions and help protect customers from fraud.

This is an opportunity to join a highly technical team where you'll have ownership from experimentation through production, working on large-scale ML systems and developing innovative approaches to fraud detection and risk modeling. You'll collaborate with experienced ML scientists and engineers to solve challenging problems using advanced statistical and machine learning techniques.

What You'll Be Doing

• Design, develop, and deploy machine learning models focused on fraud detection and risk decisioning
• Own the full ML lifecycle, from experimentation and validation through production deployment
• Work with massive datasets in distributed computing environments
• Develop and improve model evaluation frameworks and performance metrics
• Partner with cross-functional stakeholders to drive measurable business impact

What We're Looking For

• 4+ years of hands-on Machine Learning experience in a production environment
• Strong experience with Python, SQL, and Spark
• Deep understanding of machine learning, statistics, and experimental design
• Experience building models from the ground up, not just implementing existing frameworks
• Fraud, risk, payments, or trust & safety experience is required
• PhD or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field is highly preferred

Why It's Worth a Conversation

• Fully remote anywhere in the U.S.
• Competitive base salary of $140K-$175K (location dependent)
• Annual performance bonus
• Equity/stock options
• Unlimited PTO
• Strong benefits package
• Opportunity to work on mission-critical ML systems with direct business impact
• High ownership, high visibility environment where ML is a core business function