Design, build, and deploy machine learning and statistical models for threat detection, anomaly detection, fraud identification, and risk scoring using security event and telemetry data.
Engineer robust security data pipelines, including data ingestion, cleansing, feature engineering, and model monitoring, using structured and unstructured cyber data sources (e.g., logs, alerts, network flows, endpoint data).
Analyze outputs from security tools and platforms to identify control gaps, policy deviations, and emerging threat patterns, and translate findings into prioritized remediation recommendations.
Partner with cybersecurity engineering, Security Operations Center (SOC), and infrastructure teams to 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 efficacy while minimizing false positives.
Develop clear, consumable visualizations and storytelling artifacts that communicate complex analytic findings and risk scenarios to technical and non-technical stakeholders.
Create and maintain documentation for data sources, model architectures, assumptions, validation approaches, and deployment processes in line with internal governance standards.

6+ years of experience in data science or machine learning using programming languages such as Python or R to build and deploy models in production environments, preferably in cybersecurity, fraud, or risk domains.
4+ years of experience working with security-relevant datasets and tools (for example, Security Information and Event Management platforms, endpoint protection, identity and access data, or network telemetry) in an enterprise environment.
4+ years of experience with SQL and one or more big data or cloud analytics platforms (for example, Hadoop, Spark, Databricks, or cloud-native services) to process large-scale security or operational datasets.
4+ years of experience applying machine learning methods (such as classification, clustering, anomaly detection, or time series) and model evaluation techniques to real-world problems.
Demonstrated experience translating ambiguous business and security problems into analytic questions, framing hypotheses, and delivering measurable outcomes based on data-driven insights.
Bachelor’s degree or higher in Computer Science, Data Science, Statistics, Engineering, Cybersecurity, or a related quantitative field or equivalent combination of education, related experience and/or military experience.

Fuel Your Life program to support your physical, financial, social, and emotional well-being.
Paid holidays and generous time away policies.
No-cost mental health support through Employee Assistance Programs.
Living Proof program to recognize your peers’ extra effort with points redeemable for rewards.
Eight Employee Resource Groups to foster a collaborative culture and expand your network.
Unparalleled professional growth with training, development, and internal mobility opportunities.
Medical, dental, vision, life, and disability insurance options available from day one.
Retirement planning and discounted shares with the Employee Stock Purchase Plan.
Tuition assistance and reimbursement program.
Paid parental, caregiver, and military leave.

AI Engineer

Key skills