Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Build and operate large-scale data pipelines that collect, process, and improve audio datasets for AI model training. The role involves discovering data sources, optimizing data quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale data pipelines that collect, process, and improve audio datasets for AI model training. The role involves discovering data sources, optimizing data quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. Candidates need strong backend software engineering skills, Python and Bash proficiency, production systems experience, and the ability to work independently.

Build scalable, cost-efficient data pipelines and processing systems for AI model training. Responsibilities include discovering audio data sources, creating reliable ingestion pipelines, optimizing data quality and throughput, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering experience, Python and Bash proficiency, Linux expertise, and experience operating production systems.

Build and operate large-scale audio data pipelines supporting 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.

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

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, optimizing data processing for quality, throughput, and cost, and collaborating with AI scientists. Own engineering projects from discovery through implementation and continuous improvement. The role requires strong backend software engineering skills, production systems experience, and independent problem-solving in ambiguous environments.

Build and operate large-scale data pipelines for AI model training, sourcing audio data and optimizing dataset quality, processing throughput, and cost. Collaborate with AI scientists on training datasets and next-generation models, while owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering, production systems experience, and independent problem-solving in an ambiguous environment.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, improving data-processing systems, and optimizing 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, production systems experience, and independent problem-solving in an ambiguous environment.

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, and owning engineering projects end to end. The role requires strong backend software engineering skills, production systems experience, and proficiency in Python and Bash within Linux 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.