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.
Solid 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.
Solid 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: Robust 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

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

📌 Senior Applied Machine Learning Engineer Evals, Agents, Data Bengaluru
🏢 ClanX
📍 Bengaluru