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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 infrastructure to collect and process petabyte-scale audio datasets for AI model training, using GCP, Terraform, and Python.
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.
Build and scale Speechify’s data pipeline to collect and process petabyte-scale audio/text datasets for training AI text-to-speech models on GCP with Terraform.
Build and scale Speechify’s data ingestion pipeline to collect petabyte-scale audio/text datasets for training next-gen text-to-speech models using GCP, Terraform, and Python.
Build and scale Speechify’s petabyte-scale data pipeline for AI model training, integrating new audio sources and optimizing cloud infrastructure on GCP with Terraform.
Build and scale data pipelines to collect and process petabyte-scale audio/text datasets for training Speechify’s text-to-speech models on GCP using Terraform and Python.
Build and scale data pipelines to collect and process petabyte-scale audio/text datasets for training Speechify’s text-to-speech AI models, using GCP, Terraform, and Python.
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