Senior Applied AI Engineer – GenAI & Actuarial Systems
CAN, Ontario, Toronto, 200 Bloor Street East, Canada
CAD 129K-179K Senior-level Full Time
Tasks
- Apply optimization approaches
- Build predictive risk and behavior models
- Conduct sensitivity analysis
- Create structured summarization and extraction
- Define evaluation plans with backtesting and out of time testing
- Deploy and monitor machine learning models
- Design agentic workflows with traceability
- Design end to end actuarial AI solutions
- Develop forecasting and scenario models
- Develop retrieval based GenAI solutions
- Document model limitations and evidence for model risk review
- Engineer features from structured and unstructured data
- Implement drift detection and monitoring
- Implement privacy security and access controls
- Implement segmentation and anomaly detection
- Mentor junior scientists through design and code reviews
- Perform error analysis and stability testing
- Set up CI/CD and model packaging
- Translate actuarial business problems into AI use cases
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Backtesting | CI/CD | Code Reviews | Data Drift | Data Drift Detection | Data Quality | Data Quality Checks | Databricks | Deep learning | Drift Detection | Embeddings | Error Analysis | Feature Engineering | Git | Integration Testing | Logging | Machine Learning | Model Monitoring | Out of Time Testing | PyTorch | Python | Quality checks | Retrieval-Augmented Generation | SQL | Scikit-learn | Semantic Retrieval | Sensitivity Analysis | Stability Testing | TensorFlow | Unit Testing | Unit and integration testing | Vector Search
Education
N/A
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