Job Description
Every day, the models make financial decisions that affect real people. Credit approvals, fraud blocks, transaction risk scores. If a model drifts silently in production, customers get wrongly declined. If a pipeline breaks at 2am, no one catches it until the damage is done.
This role exists to make sure that does not happen.
You will own the infrastructure that takes ML models from a data scientist's notebook into production systems processing millions of events daily, and keeps them running reliably across multiple regulatory jurisdictions. Not maintaining someone else's setup. Building and owning it.
What You Will Work On
Model pipelines: Design and operate automated training, validation, deployment, and rollback workflows across our credit scoring, fraud detection, and transaction risk models
Production monitoring: Build observability for ML specific failure modes including data drift, prediction drift, an...
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