Machine Learning Engineer, Personalization
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The role
Develop and deploy ML models for language understanding using in-house and third-party LLMs, focusing on production-grade reliability.
Experiment with fine-tuning and retrieval-augmented generation (RAG) to improve model performance and user-facing content enrichment.
Collaborate with data engineers, backend engineers, and researchers to design, build, evaluate, and ship ML-powered features for recommendations.
Architect and optimize data pipelines with tools like Dataflow, Apache Beam, and Spark, enabling scalable model evaluation.
Drive disciplined experimentation, testing, and tooling to ensure high-quality assets and reliable product decisions.
Stay up-to-date with the latest ML advances and contribute to a collaborative, agile ML community.
Experiment with fine-tuning and retrieval-augmented generation (RAG) to improve model performance and user-facing content enrichment.
Collaborate with data engineers, backend engineers, and researchers to design, build, evaluate, and ship ML-powered features for recommendations.
Architect and optimize data pipelines with tools like Dataflow, Apache Beam, and Spark, enabling scalable model evaluation.
Drive disciplined experimentation, testing, and tooling to ensure high-quality assets and reliable product decisions.
Stay up-to-date with the latest ML advances and contribute to a collaborative, agile ML community.
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