Scan your resume against ATS criteria for this Senior Applied Machine Learning Engineer (Eval) - Bengaluru role at ClanX.
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.
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: Strong understanding of experiment design and statistics.
Define quality standards for Cardboard’s agent.
Build trusted evaluation datasets from real product usage.
Build offline and 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
ML & Evaluation Deep Dive
Product & Engineering Interview
Final Interview
ClanX is a recruitment partner, helping Cardboard hire Senior Applied ML Engineer, Evals & Data.
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: Strong understanding of experiment design and statistics.
Define quality standards for Cardboard’s agent.
Build trusted evaluation datasets from real product usage.
Build offline and 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
ML & Evaluation Deep Dive
Product & Engineering Interview
Final Interview
ClanX is a recruitment partner, helping Cardboard hire Senior Applied ML Engineer, Evals & Data.
How to apply for Senior Applied Machine Learning Engineer (Eval) - Bengaluru at ClanX?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
This position is open to freshers and experienced candidates.
Is this position still open?
Yes, currently active and accepting applications.
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