Machine Learning Engineer (WFH)

About the Company

The hiring company is a rapidly growing technology company focused on solving complex fraud and risk challenges at scale. Its machine learning team develops production models that support millions of real-time decisions and help protect customers from fraud.

About the Role

The company is seeking a Senior Machine Learning Engineer / Applied Scientist to develop and deploy machine learning models for fraud detection and risk decisioning. This role combines applied research, statistical modeling, and production engineering, with ownership across the full machine learning lifecycle, from experimentation and validation to deployment.

You will work with large datasets in distributed computing environments, improve model evaluation methods, and collaborate with experienced machine learning scientists, engineers, and cross-functional stakeholders. The position is suited to someone who can build models from the ground up and apply machine learning techniques to practical fraud and risk problems.

Key Responsibilities

• Design, develop, and deploy machine learning models for fraud detection and risk decisioning
• Manage the full machine learning lifecycle, from experimentation and validation through production deployment
• Work with large datasets in distributed computing environments
• Develop and improve model evaluation frameworks and performance metrics
• Apply statistical and machine learning techniques to address fraud and risk challenges
• Collaborate with cross-functional stakeholders to support measurable business outcomes
• Contribute to production machine learning systems that support real-time decisions at scale

Required Qualifications

• At least 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 machine learning models from the ground up rather than only implementing existing frameworks
• Experience in fraud, risk, payments, or trust and safety
• Must be a U.S. citizen or Green Card holder

Preferred Qualifications

• A PhD or master's degree in Computer Science, Statistics, Mathematics, or a related quantitative field is highly preferred

Location and Work Arrangement

• Location: United States
• Work Arrangement: 100% remote

Salary & Benefits

• Base Salary: $140,000–$175,000, depending on location
• Annual performance bonus
• Equity or stock options
• Unlimited paid time off (PTO)
• Benefits package