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Build petabyte-scale audio data pipelines and processing systems for AI model training. Discover data sources, improve dataset quality, throughput, and cost, and collaborate with AI scientists on next-generation models. Own engineering projects from discovery through continuous improvement while operating production systems in Linux environments. The role requires strong backend software engineering, Python and Bash proficiency, and experience with data pipelines or large-scale processing. Cloud infrastructure, Terraform, web crawlers, distributed systems, and audio or ML dataset experience are beneficial.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists on training datasets. The role requires ownership of engineering projects from discovery through continuous improvement, with strong backend development and production systems experience.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing high-throughput and cost-efficient processing systems, improving dataset quality, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering skills, Python and Bash proficiency, Linux experience, and production systems expertise.

Build scalable, reliable pipelines for sourcing and processing audio data used in AI model training. Responsibilities include discovering data sources, optimizing large-scale processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering, production systems experience, Python and Bash proficiency, and the ability to work independently in ambiguous environments.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering, production systems experience, Python, Bash, and Linux expertise, with cloud infrastructure and Terraform experience preferred.

Build and operate large-scale audio data pipelines that create high-quality datasets for AI model training. Responsibilities include discovering audio data sources, optimizing data processing for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, improving processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, optimizing data processing for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects through continuous improvement. Candidates need strong backend software engineering skills, Python and Bash proficiency, production systems experience, and the ability to work independently. Experience with web crawling, distributed processing, GCP, Terraform, machine-learning datasets, or audio processing is advantageous.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, improving processing systems, and optimizing dataset quality, throughput, and cost. Collaborate with AI scientists on training datasets and own engineering projects from discovery through continuous improvement. The role requires strong backend software engineering, Python and Bash proficiency, Linux experience, and production systems expertise.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, optimizing processing systems for quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement, with emphasis on backend software development, production systems, and scalable data processing in a distributed environment.