Senior Applied ML Engineer to own AI quality for Cardboard’s agentic video editor, building evaluation datasets, offline/online evals, regression checks, and feedback loops that turn production failures into measurable improvements.

Company Details

Requirements:
- Experience shipping and operating an LLM or agent system used by real customers.
- Solid software engineering skills in TypeScript or Python, with ability to work across both.
- Experience building evaluations, datasets, experiments, or AI quality systems.
- Strong product judgment and ability to turn vague AI quality issues into measurable problems.
- Ability to work across data, evaluation methods, model selection, and fine-tuning.
- Strong ownership as a senior individual contributor.
- Bonus: Experience with multimodal AI, video, media, or creative software.
- Bonus: Experience with human labeling, model graders, or fine-tuning.
- Bonus: Strong understanding of experiment design and statistics.

Responsibilities




- Define quality standards for Cardboard’s agent.
- Build trusted evaluation datasets from real product usage.
- Build offline and online evaluations using automated checks, model graders, and human review.
- Analyze real agent runs and identify recurring failure patterns.
- Improve agent quality through better data, evaluation methods, model selection, and fine-tuning.
- Build regression checks and release gates for important agent changes.
- Track AI quality alongside latency and cost.
- Partner with product and engineering teams to ship measurable improvements.

Job Details
Bengaluru, India

Interview Process
- Recruiter Screen
- Technical Interview
- ML & Evaluation Deep Dive
- Product & Engineering Interview
- Final Interview

Important Note
ClanX is a recruitment partner, helping Cardboard hire Senior Applied ML Engineer, Evals & Data.

📌 Senior Applied Machine Learning Engineer (Bengaluru)
🏢 ClanX
📍 Bengaluru