- Set vision and roadmap for the machine learning platform domain.
- Define standards, contracts, and shared tooling for scalable ML adoption.
- Partner with technical teams to identify workflow bottlenecks.
- Deliver capabilities like templates, CLIs, and standardized workflows.
- Advance platform features including feature governance, training-serving parity, and model release standards.
- Improve and standardize model deployment from development to production.
- Drive adoption of shared platform components across teams.
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