Director, Model Engineering & Operations
Tasks
- Automate retraining
- Collaborate on lakehouse architecture and canonical data model
- Communicate technical strategy risk and progress
- Conduct bias and fairness checks
- Define engineering standards and reusable components
- Deploy batch real time and streaming inference
- Design feature engineering and feature store
- Ensure HIPAA CMS and NCQA compliance
- Evaluate and adopt generative AI and LLM capabilities
- Implement CI/CD for ML pipelines
- Implement model monitoring drift detection and alerts
- Lead ML and AI model development
- Maintain model risk documentation for regulatory review
- Manage PHI handling access controls and audit trails
- Manage model training and versioning
- Optimize ML platform cost performance and reliability
- Own end to end MLOps lifecycle
- Productionize ML and AI models
- Translate business problems into scoped ML engineering initiatives
- Use champion challenger model evaluation
Perks/Benefits
- N/A
Skills/Tech-stack
Azure | Bias and fairness | CCDA | CI/CD | Champion Challenger | Databricks | Delta Lake | Drift Detection | Embeddings | FHIR | Feature Store | Fraud Waste and Abuse | GenAI | HCC | HEDIS | HIPAA | HL7 | Infrastructure as Code | LLM | MLOps | MLflow | Model Monitoring | Prompt engineering | Python | RAF) | Retrieval-Augmented Generation | SQL | Spark | Stars | Unity Catalog | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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