Senior Applied Machine Learning Engineer - Bengaluru
Role Overview
Own AI quality for Cardboard’s agentic video editor and turn production failures into measurable improvements.
Work on agentic tools that understand user requests, work with media, and make real edits on the timeline.
Key Skills for This Role
Full Job Posting
Role overview
Own AI quality for Cardboard’s agentic video editor and turn production failures into measurable improvements.
Work on agentic tools that understand user requests, work with media, and make real edits on the timeline.
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 qualifications
- Experience with multimodal AI, video, media, or creative software.
- Experience with human labeling, model graders, or fine-tuning.
- 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.
Interview process
- Recruiter screen.
- Technical interview focused on ML and evaluation.
- ML and evaluation deep dive.
- Product and engineering interview.
- Final interview.
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