Red Hat
Open-source MLflow, focused on agent observability and on how evaluations are executed.
- Trace archival and streaming retrieval, evaluation job execution, and the communication between the server and the client SDK.
- Designed a pluggable execution framework for evaluation and scoring jobs, with process isolation, cancellation and timeout semantics held under test.
- Partnering with other Red Hat product teams to land their MLflow integrations, translating requirements into upstream changes and carrying them through public review.
- Maintaining Red Hat's downstream MLflow distribution shipped in OpenShift AI: release engineering, CI stability and dependency remediation.