Requirements

- Experience shipping and operating an LLM or agent system used by real customers.

- Strong 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: 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

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