We're looking for a machine learning engineer to take models past the notebook - into production, under load, with someone watching how they behave.
What you'll do
- Train, evaluate and ship models against real product problems.
- Build the serving path: inference, latency, versioning and rollback.
- Watch what happens after launch - drift, quality regressions and cost.
- Work with engineering and product on where a model helps and where it doesn't.
What we're looking for
- Experience putting at least one model into production and living with it afterwards.
- Strong Python and comfort with the modern ML tooling.
- Honesty about evaluation - knowing when a metric is lying to you.