Staff ML Engineer, Content Mining
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El puesto
Lead the multi-quarter technical vision and execution for source discovery, content acquisition optimization, and content understanding.
Architect scalable ML systems to extract structured attributes at large scale, including NLP/LLM models and shared features.
Own end-to-end development from training and fine-tuning to production deployment, with focus on latency and cost efficiency (quantization, distillation, caching).
Set engineering standards, review designs, and mentor a 5-person MLE team to raise technical depth and collaboration.
Define robust offline/online evaluation, labeling standards, and automated regressions; run A/B and canary/shadow experiments.
Define and meet SLOs for data quality and model performance; drive impact on user engagement and revenue, and lead incident responses.
Architect scalable ML systems to extract structured attributes at large scale, including NLP/LLM models and shared features.
Own end-to-end development from training and fine-tuning to production deployment, with focus on latency and cost efficiency (quantization, distillation, caching).
Set engineering standards, review designs, and mentor a 5-person MLE team to raise technical depth and collaboration.
Define robust offline/online evaluation, labeling standards, and automated regressions; run A/B and canary/shadow experiments.
Define and meet SLOs for data quality and model performance; drive impact on user engagement and revenue, and lead incident responses.
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