Senior Applied ML Engineer, Evals & Data

ABOUT - We're building the future of storytelling and video editing. - We're a small team that moves fast and builds things we're proud of. - We care obsessively about taste: in design, in product, in every detail. - We're solving these https://www.cardboard.ai/hard-problems hard problems. - We're backed by a Tier-1 global fund, YC, and founders of billion dollar companies. AI ENGINEERING Cardboard is a video editor you can talk to. Our agent makes real edits on the timeline. When it gets one right, it feels like magic. When it gets one wrong, it costs someone their afternoon. We're hiring a Senior Applied ML Engineer to own how good the agent is: turn real failures into evals, evals into a bar the team trusts, and that bar into shipped improvements. This isn't research-only, prompt-only, or QA. WHAT YOU'LL OWN - What "good" means for our agent, and datasets built from real usage. - Offline and online evals: automated checks, model graders, and human review. - Regression gates, and quality tracked alongside latency and cost. - Which models the agent runs on. WHO YOU ARE - You've shipped an LLM or agent system that real customers used. - You've built evals, datasets, or AI quality systems before. - You can turn "the agent feels dumb" into a number, then move it. - Strong in TypeScript or Python. No PhD needed. - Bonus: multimodal AI, video, or fine-tuning. HOW WE WORK - You own outcomes, not tickets: decide what to build, ship it, and check it worked. - You talk to users and look at the data. - You build with AI agents every day, and you're the taste and judgment in the loop. WHAT SUCCESS LOOKS LIKE Within your first six months: - The team trusts a quality baseline for our main agent workflows. - Production failures regularly become eval cases. - We can show measurable improvements in key editing workflows. WHAT YOU GET You'd be surrounded by people who are absurdly good at what they do. One started coding at 11 and shipped an app with 6M+ downloads in high school. One got into CS engineering at 14 and has been working on distributed systems for 8+ years. One's an ex-founder who took a company to 1.2M users and $300M+ in transactions. That's the team. We're looking for someone who'll raise the bar on how we measure and improve AI quality. Apart from that you'd get: - Competitive salary and founding-team equity. - Unlimited tokens across every AI model. Use whatever you want, as much as you want. - A healthy budget for AI tools and any peripherals you need to do your best work.