AI Engineer

What you'll do

• Design, build, and deploy machine learning models for threat detection, fraud identification, and risk scoring.
• Engineer robust security data pipelines for ingestion, cleansing, feature engineering, and model monitoring.
• Analyze security tool outputs to identify control gaps and provide prioritized remediation recommendations.
• Embed AI and advanced analytics into security controls, playbooks, and incident response workflows.
• Conduct model performance evaluations, bias and drift analysis, and continuous tuning to improve detection.
• Create visualizations and storytelling artifacts to communicate complex analytic findings to technical and non-technical stakeholders.
• Maintain documentation for data sources, model architectures, and deployment processes in line with governance standards.

What we're looking for

• 6+ years of experience in data science or machine learning using Python or R to build and deploy models in production environments.
• 4+ years of experience working with security-relevant datasets and tools in an enterprise environment.
• 4+ years of experience with SQL and one or more big data or cloud analytics platforms like Hadoop, Spark, or Databricks.
• 4+ years of experience applying machine learning methods and model evaluation techniques to real-world problems.
• Bachelor’s degree or higher in Computer Science, Data Science, Statistics, Engineering, Cybersecurity, or a related quantitative field.
• Must possess valid and unrestricted U.S. work authorization.
• Experience applying AI or advanced analytics to cybersecurity use cases (preferred).
• Experience in the financial services or payments industry working with sensitive data (preferred).
• Experience with MLOps practices and tooling in a regulated environment (preferred).
• Professional certifications such as CISSP, CCSP, or recognized data science/cloud certifications (preferred).