Top Tech Jobs & Startup Jobs

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable 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 in a distributed, asynchronous environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving 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, Python and Bash proficiency, production systems experience, and independent problem-solving.

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 skills, production systems experience, and proficiency in Python, Bash, and Linux, with preferred experience in web crawling, distributed processing, GCP, Terraform, and audio or ML training data.

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.

Build and operate large-scale audio data pipelines for AI model training. Discover new data sources, optimize data-processing systems for quality, throughput, and cost, and collaborate with AI scientists on training datasets. Own engineering projects from discovery through continuous improvement in a distributed environment.

Build and operate large-scale audio data pipelines supporting AI model training. Responsibilities include discovering data sources, optimizing processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects through continuous improvement. The role requires strong backend software engineering, production systems experience, and proficiency in Python and Bash on Linux. Experience with web crawling, distributed processing, GCP, Terraform, machine learning datasets, or audio processing is beneficial.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, optimizing data-processing systems for quality, throughput, and cost, collaborating with AI scientists on training datasets, and owning engineering projects through continuous improvement. The role requires strong backend software engineering, production systems experience, and proficiency in Python and Bash within Linux environments.

Build scalable data pipelines and processing systems for AI model training. Responsibilities include discovering audio data sources, improving dataset quality and processing efficiency, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering, production systems experience, and proficiency in Python, Bash, and Linux, with preferred experience in cloud infrastructure, Terraform, web crawlers, distributed processing, and audio data.

Build scalable data pipelines and processing systems for AI model training datasets. Discover audio data sources, improve data quality, throughput, and cost, and collaborate with AI scientists on next-generation models. Own engineering projects from discovery through continuous improvement, operating production systems in ambiguous environments.

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 on training datasets. The role requires ownership of engineering projects from discovery through continuous improvement in a distributed environment.