AI/ML Deployment and Enablement Leader
Tasks
- Define MLOps practices including CI CD and model registry
- Define unified AI stack and architectural patterns
- Design scalable modular AI ecosystem
- Enable and scale adoption of AI platforms and tools
- Ensure reliability latency and regulatory compliance
- Establish AI playbooks and best practice frameworks
- Evaluate AI technologies and define adoption roadmaps
- Govern end to end AI lifecycle
- Implement automated rollback and governance
- Lead self service AI platform development
- Manage model governance versioning data lineage explainability and auditability
- Oversee high availability AI model deployments
- Own on prem AI platform stack evolution and operating model
- Set AI standards and execution mechanisms
- Set SLAs KPIs and observability standards for AI services
Perks/Benefits
- 401k employer match
- Adoption Assistance
- Dental insurance
- Health insurance
- Life insurance
- Long-term disability
- Paid Holidays
- Paid vacation
- Parental leave
- Short-term disability
- Vision insurance
Skills/Tech-stack
Amazon Web Services | Artificial Intelligence | Auditability | Automated rollback | Azure AI | CI/CD | Cloud Computing | Data Lineage | Enterprise Architecture | Explainability | High Availability | Latency optimization | MLOps | Machine Learning | Microsoft Azure | Model Governance | Model Registry | Observability | Web Services
Education
Regions
Countries
States
Cities
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