Machine Learning Research Intern at Bell Labs collaborating with scientists on innovative machine learning research and thesis projects in AI and telecommunications.
About the role
- 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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