Director of Software Engineering (MLOps & ML Governance)
KS Overland Park, United States
USD 138K-200K Executive-level Full Time
Tasks
- Align strategies to AI ML roadmaps
- Automate ML testing
- Build enterprise MLOps platforms
- Create model documentation
- Deploy models and manage retraining
- Design and develop software systems
- Detect model drift
- Develop and grow engineering organization
- Develop long-term technology strategy
- Ensure audit readiness
- Ensure regulatory compliance for AI ML
- Establish model observability
- Govern model deployment
- Implement ML CI CD pipelines
- Implement explainability
- Lead MLOps delivery
- Manage ML model lifecycle
- Manage engineering and MLOps teams
- Manage infrastructure budgets
- Manage model risk controls
- Manage model versioning
- Monitor fairness and bias
- Monitor models in production
- Validate ML models
Perks/Benefits
- 401k match
- Business resource groups
- Dental insurance
- Family and medical leave
- Life insurance
- Medical insurance
- Paid disability
- Paid parental leave
- Paid time off
- Paid volunteer time
- Tuition reimbursement
- Vision insurance
Skills/Tech-stack
AWS | Audit Readiness | Automated testing | Azure | CI/CD | Cloud Computing | Cloud platform | Compliance | Data Governance | Distributed Systems | Docker | Drift Detection | Enterprise Risk | Enterprise Risk Management | Explainable AI | Fairness metrics | Google Cloud | Google Cloud Platform | Information security | Infrastructure as Code | Kubernetes | ML Governance | MLOps | Machine Learning | Model Deployment | Model Monitoring | Model versioning | Observability | Privacy | Retraining | Risk Management | Software Engineering | “as-code”
Education
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