Machine Learning Engineer II, Fraud Risk Modeling

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge:
Great Company, Great Culture, Great Rewards and Great Careers.

GEICO’s Fraud Risk Modeling team is building a centralized, multi-modal fraud defense ecosystem that unifies claims, payment, and identity risk assessment. As a Machine Learning Engineer II
, you will take ownership of critical ML components, deliver production-grade models, ensure our fraud detection capabilities are robust and high-performing, and help evolve our fraud platform at scale.

This role is ideal for engineers who are comfortable operating independently, making technical tradeoffs, and delivering reliable ML systems in production.

• Design, implement, and maintain production ML models and features for fraud risk assessment.
• Own model components across the full lifecycle: from data preparation and feature engineering to deployment and monitoring.
• Improve model accuracy, stability, and interpretability through experimentation and iteration.

• Build and enhance scalable ML pipelines supporting batch and real‑time fraud decisioning.
• Build monitoring and alerting to detect data drift, model degradation, and system failures.
• Optimize performance and reliability of ML services under production traffic.

• Collaborate with Senior and Staff engineers on system design and architecture decisions.
• Write high-quality, well‑tested code and contribute to shared ML libraries and tooling.
• Provide guidance and code reviews for junior engineers (MLE I).
• Translate business and fraud domain requirements into technical ML solutions.

• Participate in on‑call rotations or incident response related to ML services.
• Ensure ML systems meet security, privacy, and regulatory requirements.
• Contribute to technical documentation and best‑practice sharing across teams.

• Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
• 3+ years of hands‑on experience building, deploying, and operating ML systems in production.
• Strong proficiency in Python (and/or Java) with a focus on production‑quality code.
• Experience with end‑to‑end ML lifecycle management, including monitoring and retraining.
• Familiarity with distributed systems, data pipelines, and cloud‑based ML infrastructure.

• Experience in Fraud Detection, Risk Modeling, Trust & Safety, or Identity systems.
• Hands‑on experience with big‑data technologies (Spark, Snowflake, Redis, Kubernetes).
• Familiarity with workflow orchestration tools like Airflow.
• Exposure to feature stores, real‑time ML serving, or graph‑based modeling.
• Familiarity with model explainability, fairness, or governance in regulated environments.

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The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

At GEICO, we help our customers through life’s twists and turns. Our mission is to protect people when they need it most and we’re constantly evolving to stay ahead of their needs.

We’re an iconic brand that thrives on innovation, exceeding our customers’ expectations and enabling our collective success. From day one, you’ll take on exciting challenges that help you grow and collaborate…