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Build and scale Speechify’s data ingestion pipeline to collect petabyte-scale audio/text datasets for training next-gen text-to-speech models on GCP with Terraform.
Builds and optimizes petabyte-scale data pipelines for AI model training, focusing on audio data collection, cloud infrastructure (GCP/Terraform), and cost-efficient workflows to fuel Speechify’s text-to-speech AI.
Build and scale Speechify’s data infrastructure to collect and process petabyte-scale audio datasets for training AI text-to-speech models.
Build and scale Speechify’s petabyte-scale data pipeline for AI model training, integrating web crawlers, GCP infrastructure, and Terraform to collect and process audio/text data.
Builds and optimizes petabyte-scale data pipelines to fuel AI models by sourcing audio data, managing cloud infrastructure (GCP/Terraform), and collaborating with researchers to improve cost/quality tradeoffs for Speechify’s text-to-speech products.
Build and scale Speechify’s data infrastructure to collect and process petabyte-scale audio datasets for AI model training, using GCP, Terraform, and Python.
Works on data collection for AI model training, finding new audio data sources, operating GCP infrastructure with Terraform, and collaborating with scientists. Core technologies include GCP, Terraform, Python, and large-scale data processing.
Build and scale Speechify’s data pipeline to collect and process petabyte-scale audio/text datasets for AI model training, using GCP, Terraform, and Python.
Build and scale Speechify’s data ingestion pipeline to collect petabyte-scale audio datasets for AI model training, using GCP, Terraform, and Python.
As a Product Engineer on Anthropic's Applied AI team, you'll develop bespoke LLM solutions for Japanese enterprises using Claude, acting as a technical advisor, architecting solutions, and supporting customer onboarding. Core technologies include LLMs (Claude) and Python.
Build and scale Speechify’s data ingestion pipeline to collect petabyte-scale audio/text datasets for AI model training, using GCP, Terraform, and Python.
Build and scale Speechify’s petabyte-scale data pipeline for AI model training, integrating cloud infrastructure, web crawlers, and data acquisition to power next-gen text-to-speech models.
Builds and optimizes petabyte-scale data pipelines for AI model training, focusing on audio data collection, cloud infrastructure (GCP/Terraform), and cost-efficient workflows to enhance Speechify’s text-to-speech products.
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