AI/ML Engineer
Tasks
- Analyze data sources for fraud detection
- Conduct research on model portfolio impact
- Continuously improve machine learning models
- Deploy machine learning models
- Develop Python code for financial decisioning
- Develop end-to-end machine learning models
- Integrate models into production services
- Operate training and deployment infrastructure
- Provide evidence for production model audits
- Research and develop statistical behaviors
- Strategize and implement portfolio performance improvements
Perks/Benefits
- N/A
Skills/Tech-stack
Cloud Computing | Data Science | Deep learning | Distributed Systems | Fraud Detection | Machine Learning | Model Deployment | Model Monitoring | Python | REST | Risk Management | SQL | Statistical Analysis
Education
Master of Science | Master of Science in Computer Science | Master of Science in Data Science | Master of Science in Mathematics | Master of Science in Statistics
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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