Applied ML Engineer

The Role

We’re looking for an Applied ML Engineer to build systems at the intersection of machine learning research and production software.

This is an end-to-end engineering role. You should be comfortable reading a research paper, identifying what is actually testable, building the smallest useful experiment, evaluating it rigorously, and turning the result into a production system that users can interact with.

You’ll work across model evaluation, model internals, inference infrastructure, backend systems, and product interfaces. The goal is not simply to reproduce research. It is to turn promising methods into reliable, measurable, and usable products.

What You’ll Do

• Reproduce and evaluate research methods using open-weight and API-accessible models.

• Design evaluation datasets, probes, scoring methods, baselines, calibration tests, and experiment harnesses.

• Work directly with model weights, logits, hidden states, activations, model APIs, and inference infrastructure when required.

• Build and extend our evaluation infrastructure, including runners, judges, persistence, experiment orchestration, and reporting.