Machine Learning Engineer II developing production-grade ML models for fraud detection at GEICO. Collaborating on system architecture and ensuring optimal performance of fraud assessment systems.
Responsibilities
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)
Requirements
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
Benefits
Health insurance
401K savings plan vested from day one with 6% match
Performance and recognition-based incentives
Tuition assistance
Mental healthcare
Fertility and adoption assistance
Workplace flexibility
GEICO Flex program for remote work up to four weeks per year
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