Do.ML is invite-only. Sign in with your LinkedIn account to get started.
The team needs a structured, low‑disruption workflow for upgrading software dependencies. The workflow must clarify strategy, risks, testing, rollback, and communication while accounting for breaking changes and CI processes. The goal is to ensure predictable releases using practical, calm guidance.
The goal is to assist an MLOps Group Manager in producing a complete, reliable release plan for deploying an updated machine learning model to production. The workflow must transform model change summaries, performance metrics, infrastructure constraints, and compliance requirements into structured release artifacts. The final output ensures safe deployment through validation, canary planning, monitoring design, rollback preparation, and stakeholder communication.
R&D Group Manager, MLOps at JFrog 🐸
Data Tech Lead at Riskified