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 hard problems.
We're backed by a Tier-1 global fund, YC, and founders of billion dollar companies.
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 ownWhat "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.
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.
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.
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.
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.
Skills Required
- 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 ability to turn unclear quality problems into measurable improvements
- Experience with multimodal AI, video, media, or creative software
- Experience with human labeling, model graders, or fine-tuning
- Knowledge of experiment design and statistics
What We Do
Cardboard, Inc. develops an agentic, browser-based AI video editor for growth and marketing teams and serious creators. Users can describe an intended edit in natural language, while the product cuts, captions, reframes, composes, and searches footage. Its browser-native workflow combines a multi-layer timeline, collaboration, auto-captioning, voiceover and music generation, and exports for professional finishing applications, helping teams produce and iterate videos faster.







