Overview
GEICO is transforming the insurance industry with Artificial Intelligence, and the Fraud Risk Modeling team is at the center of this evolution. As a Machine Learning Engineer I, you will contribute to building and operating production machine learning models that help protect millions of customers from fraud.
This is an early-career to mid-level role for engineers who are excited to work on real-world ML systems, learn large-scale production practices, and grow within a collaborative, mission-driven team.
Key Responsibilities
Machine Learning Development & Implementation
- Implement, test, and maintain machine learning models used in fraud detection and risk assessment.
- Support feature engineering, data validation, and model experimentation under guidance from senior engineers.
- Assist in deploying models into production using established MLOps pipelines and tooling.
Data & Pipeline Contributions
- Work with structured and semi-structured data to build reliable training and inference datasets.
- Contribute to batch and near-real-time ML pipelines for fraud scoring and decisioning.
- Help monitor data quality, model performance, and system reliability.
Engineering Best Practices
- Write clean, well-tested, maintainable code in Python (and/or Java).
- Participate in code reviews, design discussions, and post-incident reviews.
- Follow security, compliance, and governance standards required in a regulated environment.
Collaboration & Learning
- Collaborate closely with data scientists, product managers, and senior ML engineers.
- Learn industry best practices for model lifecycle management, monitoring, and experimentation.
- Actively seek feedback and continuously improve technical and domain knowledge.
Minimum Qualifications
- Bachelor’s degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
- 1–3 years of hands-on experience building or supporting ML models or data pipelines (internships count).
- Proficiency in Python and familiarity with ML libraries (e.g., scikit-learn, PyTorch, TensorFlow).
- Basic understanding of ML model training, evaluation, and deployment concepts.
- Strong problem-solving skills and eagerness to learn production ML systems.
Preferred Qualifications
- Exposure to fraud detection, risk modeling, or anomaly detection problems.
- Familiarity with SQL and large-scale data platforms (e.g., Spark, Snowflake).
- Experience with cloud platforms (AWS or Azure) or containerized environments.
- Interest in responsible AI, model monitoring, and explainability.
Annual Salary
$90,000.00 - $185,000.00
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.
At this time, GEICO will not sponsor a new applicant for employment authorization for this position.
