My MLOps skills, with evidence for each one.

I package services with Docker and define Kubernetes workloads. In SignalOps, I test queue retries, dead-letter handling, and a paper-only execution boundary.

I use purged walk-forward evaluation, calibrated baselines, and signed reports. I bind each candidate to its inputs and protect a final holdout from repeated tuning.

I run unit and integration tests, verify artifact checksums, scan policy and dependencies, and block promotion when an evidence check fails.

I define calibration, drift, latency, and feed-health signals. SignalOps tests shadow evaluation, incident records, rollback, and reconciliation.

I sign model evidence, chain audit events, check dataset rights, and verify artifacts and promotion policy before admission.

I validate schemas and timestamps, reconcile sources, and bind point-in-time features and label availability to immutable manifests.

I bring Python, SQL, REST services, algorithms, and full-stack engineering to this work, supported by degrees in computer science and information technology.