Sr. Data Science Engineer, Siri Core Modeling

As part of the work on machine-generated dialog we are developing novel measurements of its quality. These include cutting-edge llm-judges for aspects like groundedness (lack of hallucinations), Siri Tone and Style (a suite of Design requirements), Safety, and others.

Description

To measure our progress on this front, we need to track the state of our dataset composition, accuracy of llm-judges, human expert review results in a central and visual representation. A DRI for Metrics and Reporting will:

Minimum Qualifications

M.S. or Ph.D. in Computer Science, Data Science, Data Engineering 3+ years in data-science and/or data-engineering (iceberg, pandas python, Tableau or equivalent, data collection and visualization) 2+ years of python coding Good understanding of metrics, crowd science, annotation analysis, statistics Ability to work independently and cross-functionally to integrate in partner team reporting systems and pipelines Excellent communication skills and the ability to thrive in a highly collaborative work environment Good engineering practices to create sustainable and easy to use metric reporting pipelines

Preferred Qualifications

Experience with writing and architecting production level code Deep understanding of Machine Learning concepts Experience in Model training and/or evaluation Good engineering practices to create sustainable and easy to use metric reporting pipelines Attunement to computational linguistics, language quality is a plus

Responsibilities

Build an easy to use dashboard for our datasets - requires integration with other teams Build dashboards to visualize our status Help define useful metrics Build tools to facilitate processing of human review results (inter-annotator agreement, storage, selection of the most useful data points for human expert review) Build tools and pipelines to streamline quality measurement processes

Eeo Content

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