VP of AI, ML and Data Strategy
Tasks
- Architect deploy and operate production ML systems for real time inference
- Build and scale data science AI data engineering and BI engineering org
- Connect ML data and BI investments to customer outcomes
- Drive model lifecycle including retraining evaluation and validation
- Drive performance management and career development
- Establish monitoring alerting and incident response for ML and pipelines
- Establish responsible AI evaluation benchmarking validation and regression harnesses
- Lead build vs buy decisions across ML and data stack
- Lead external partnerships for generative AI cloud and model providers
- Lead foundational generative AI data and LLM and agent infrastructure
- Manage managers and tech leads
- Own LLM provider vector store and orchestration and agent infrastructure decisions
- Own business intelligence delivery and analytics surfaces
- Own data platform including data lake warehouse orchestration and transformation
- Own production machine learning for delivery promise carrier selection fulfillment optimization and simulation
- Own reliability and cost tradeoff posture
- Own technical hiring bar and interview loop design
- Run quarterly and annual function planning with roadmap alignment
- Set ML data and BI multi year strategy
- Set and enforce engineering and analytical standards
- Set technical direction for LLM integration into predictive models
Perks/Benefits
Skills/Tech-stack
AWS S3 | Amazon Redshift | Apache Airflow | DBT | Datadog | Deep learning | Generative AI | LLM orchestration | Machine Learning | PyTorch | Python | SQL | Scikit-learn | Vector Databases | XGBoost
Education
N/A
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