Hybrid Fraud ML Engineer

Talentify; Charlotte (NC); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Hybrid Work Opportunities

Flexible Time Off

Career Development & Mentoring

Health & Wellness Benefits

Community volunteering & philanthropy

Employee Recognition Programs

Job summary

Q2, a leader in digital banking and lending, seeks a Machine Learning Engineer for risk and fraud. You will build production ML systems to detect fraud at scale, collaborating with data scientists and engineers to deploy reliable models.

You’ll gain hands-on experience across model development, evaluation, deployment, and monitoring, solving real customer problems with rigor and impact.

Qualifications

• Bachelor's degree and 2+ years in ML model development and deployment.
• Strong knowledge of statistics, optimization, probability theory, and experimental methodologies.
• Proficiency in Python, R, or Java.
• Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn).

Responsibilities

• Research emerging fraud patterns and translate into detection approaches.
• Build ML products across identity, behavior, and transaction fraud with customers.
• Create real-time, low-latency ML infrastructure and improve reliability and scale.
• Maintain pipelines for training, evaluation and inference with data scientists.
• Write clean, tested production-grade code following best practices.
• Monitor and troubleshoot production ML systems and data pipelines.

Skills

Python

R

Java

Statistics

ML Deployment

Education

Bachelor's degree in related field

Tools

TensorFlow

PyTorch

scikit-learn

Cloud platforms

Job description

Q2, a leader in digital banking and lending, seeks a Machine Learning Engineer for risk and fraud. You will build production ML systems to detect fraud at scale, collaborating with data scientists and engineers to deploy reliable models.

You’ll gain hands-on experience across model development, evaluation, deployment, and monitoring, solving real customer problems with rigor and impact.