Machine Learning Engineer
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El puesto
Take ownership of end-to-end ML features, from problem discovery to deployment and monitoring, delivering tangible business impact.
Collaborate with product, design, and engineering to scope work and define clear success metrics for each feature.
Develop and operate ML models across the lifecycle, including experimentation, training, validation, serving, and retraining.
Build production-grade data pipelines, data contracts, and robust monitoring/incident response to maintain service reliability.
Apply ML to time series data, embeddings, and foundation models for tasks like revenue forecasting, churn analysis, personalization, and NLP.
Communicate clearly with both technical and business stakeholders in a remote, cross-functional environment.
Collaborate with product, design, and engineering to scope work and define clear success metrics for each feature.
Develop and operate ML models across the lifecycle, including experimentation, training, validation, serving, and retraining.
Build production-grade data pipelines, data contracts, and robust monitoring/incident response to maintain service reliability.
Apply ML to time series data, embeddings, and foundation models for tasks like revenue forecasting, churn analysis, personalization, and NLP.
Communicate clearly with both technical and business stakeholders in a remote, cross-functional environment.
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