Applied AI Engineer

Role overview

Develop applied machine learning models that analyze AI assistants’ answers at scale and turn the results into useful actions for merchants. The role combines model development with rigorous evaluation, with an emphasis on detecting quality changes and making outputs understandable and actionable.

Responsibilities

- Build and evaluate the models that power the product. - Create evaluations that reveal when model performance degrades, ideally before customers encounter the change. - Translate model outputs into clear recommended actions for users. - Assess whether model results are useful in practice, beyond their technical scores or presentation.

Requirements

- Hands-on applied machine learning or large language model experience, including retrieval and evaluation. - Ability to assess real-world model behavior beyond prototypes and demonstrations. - A skeptical, evidence-driven approach to results, including designing tests that could disprove an apparent improvement. - Focus on practical usefulness when choosing methods and evaluating outputs.