VP AI ML Engineering, Medicare & Retirement
USD 200K-343K Executive-level Full Time
Tasks
- Build enterprise AI ML platforms
- Define AI/ML strategy
- Deliver production-grade AI systems
- Deploy and monitor AI models
- Develop AI talent and workforce strategy
- Drive scaled AI first engineering adoption
- Embed AI across business value streams
- Embed AI into SDLC and operational workflows
- Enable real time decisioning and batch analytics
- Ensure AI compliance and privacy
- Establish model validation testing and monitoring
- Govern models with security and risk teams
- Implement responsible AI practices
- Lead AI blueprint transformation
- Monitor transformation progress risks and outcomes
- Optimize AI performance and cost
- Prioritize high-value AI use cases
- Scale pilots into enterprise platforms
- Standardize MLOps and AI pipelines
- Translate business problems into AI solutions
- Use NLP NLU intent classification computer vision and speech recognition
Perks/Benefits
Skills/Tech-stack
AI SDLC | APIs | AWS | Application Security | Artificial Intelligence | Automatic Speech Recognition | Azure | Batch Analytics | Cloud Native | Cloud platform | Computer Vision | Data Processing | Deep learning | DevOps | Enterprise Architecture | Generative AI | Google Cloud | Google Cloud Platform | Intent Classification | LLM | Language Processing | Language Understanding | MLOps | Machine Learning | Microservices | Model Monitoring | Model Validation | Natural Language | Natural Language Processing | Natural Language Understanding | Optimization | Probability | Probability theory | Real Time | Real-time Data | Real-time Data Processing | SDLC | Speech Recognition | Statistics
Education
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