Director, Decision Science AI/ML Engineering & Ops
USA - CA - 820 S Flower St, United States
USD 217K-306K Executive-level Full Time
Tasks
- Architect MLOps roadmap
- Build KPI dashboards for model reliability
- Build reusable feature engineering and model templates
- Create automated pipelines for training and deployment
- Create scalable batch and callable services
- Design feature stores and governance
- Drive explainability for deployed models
- Embed security privacy explainability responsible AI by default
- Enable model deployment into SaaS products
- Ensure operational reliability and incident response
- Establish intake prioritization for reuse and standardization
- Establish production first culture
- Implement automated model monitoring and sustainment
- Implement automated testing validation suites
- Lead and mentor AI/ML engineers
- Manage security and compliance requirements
- Productionize decision science models and algorithms
- Remediate technical debt in ML pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
AI/ML | AI/ML Pipelines | Artificial Intelligence | Automated testing | Automation | Cloud Computing | Data Drift | Data Quality | Explainable AI | Feature Stores | Generative AI | Incident Management | KPI Dashboards | ML pipelines | MLOps | Machine Learning | Model Governance | Model Monitoring | Optimization | Optimization Algorithms | Privacy | Responsible AI | Security | Simulation | Simulation Modeling | Software Architecture | Software Engineering | Statistical Analysis | Statistical modeling
Education
N/A
Regions
Countries
States
Cities
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