About the role
Cardboard is hiring a Senior Applied ML Engineer to own how the company measures and improves the quality of its AI video-editing agent. You'll study real agent runs, turn important failures into evaluation cases, and measure whether changes actually make the product better - not a research-only, prompt-only, or QA role, but hands-on ownership of quality end to end.
What you'll do
Define quality standards and build trusted evaluation datasets from real product usage
Build offline and online evaluations, including automated checks and human review
Analyze model and agent failure patterns, then improve quality through better data, evaluation methods, model selection, and fine-tuning where useful
Add regression checks and release gates while tracking quality, latency, and cost
Work closely with product and engineering to ship quality improvements
What we're looking for
5++ years of relevant experience
Experience shipping and operating an LLM or agent system used by real customers
Strong software engineering skills in TypeScript or Python, with the ability to work across both
Experience building evaluations, datasets, experiments, or AI quality systems
Strong product judgment and the ability to turn unclear quality problems into measurable improvements
5+ years of experience
Nice to have
Experience with multimodal AI, video, media, or creative softwareExperience with human labeling, model graders, or fine-tuningGood knowledge of experiment design and statistics