Service
ML / RL engineering
Training, evaluation, deployment infrastructure for ML systems.
- Typical engagement
- 8-16 weeks
- Capabilities
- data pipelineseval harnessesmodel registriesserving infrastructure
We build data pipelines, eval harnesses, model registries, deployment plumbing.
The unglamorous plumbing of ML that makes a model recoverable, comparable, and shippable.
Most projects don’t fail at training. They fail when nobody can reproduce last month’s run, or the eval set has drifted, or the staging model behaves differently from prod for reasons no one logged.
We build the parts that prevent that. The training code we touch we leave well-typed and well-tested; the training code we don’t touch we wrap.