Senior Data Architect

À propos de ce poste

Accountabilities Own the Training Environment data architecture end-to-end: dataset design and schema for all ML training pipelines, including dialog corpora for LLM training, conversational steps for NLU models, annotated evaluation sets, and whole-call recordings for speech-to-speech model development. Define and govern data selection and sampling strategy: establish criteria that determine which production conversations have the highest training value, including diversity-optimized sampling, confidence-based filtering, edge-case prioritization, and deduplication strategies. Build and maintain the data catalog and dataset discovery infrastructure: enable ML engineers across LLM, NLU, Speech, and Agentic teams to find, understand, and use training data without friction. Define annotation …

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