Director, Decision Science AI/ML Engineering & Ops
USA - CA - 820 S Flower St, United States
USD 228K-306K Executive-level Full Time
Tasks
- Architect scalable MLOps platforms
- Build feature stores
- Co design scalable batch or callable services
- Create automated testing and validation
- Define MLOps roadmap
- Design reusable model templates
- Drive production first culture
- Embed model explainability
- Ensure operational reliability
- Ensure responsible AI governance
- Ensure security and privacy by default
- Establish KPI dashboards
- Implement automated model monitoring
- Lead AI ML engineering team
- Manage intake and prioritization
- Optimize cloud compute costs
- Productionize decision science for SaaS
- Reduce technical debt
- Remediate ML pipeline failures
- Support responsible scaling of AI ML workloads
Perks/Benefits
- N/A
Skills/Tech-stack
AI Engineering | API Services | Artificial Intelligence | Automated testing | Batch Processing | Cloud Computing | Data Drift | Data Drift Detection | Data Quality | Data quality monitoring | Debt management | Deep learning | Drift Detection | Explainable AI | Feature Engineering | Feature Store | GenAI | KPI Dashboards | MLOps | Machine Learning | Model Governance | Model Monitoring | Model Validation | Observability | Optimization | Pipeline Orchestration | Privacy | Quality monitoring | Responsible AI | SaaS | Security | Simulation | Statistical modeling | Technical Debt | Technical Debt Management
Education
N/A
Regions
Countries
States
Cities
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