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. Responsibilities include discovering data sources, optimizing processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build scalable audio data pipelines and large-scale processing systems for AI model training. Discover data sources, optimize 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 an independent, distributed environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable ingestion and processing systems, optimizing data 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, and proficiency in Python, Bash, and Linux.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable data-processing systems, optimizing data quality, throughput, and cost, and collaborating with AI scientists. The role owns engineering projects end to end and requires strong backend software engineering, production systems, and independent problem-solving skills.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering audio 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, autonomous environment.

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

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. The role owns engineering projects from discovery through continuous improvement and requires strong backend software engineering skills, production systems experience, and proficiency with Python, Bash, and Linux. Experience with web crawling, distributed processing, GCP, Terraform, machine-learning datasets, and audio processing is beneficial.

Build scalable data pipelines and processing systems for AI model training. Discover audio data sources, optimize data quality, throughput, and cost, and collaborate with AI scientists on next-generation models. Own engineering projects from discovery through continuous improvement. The role requires strong backend software engineering skills, production systems experience, and the ability to work independently in ambiguous environments.

Build and operate large-scale data pipelines that collect, process, and optimize audio datasets for AI model training. The role involves discovering data sources, improving data quality, throughput, and cost efficiency, partnering with AI scientists, and owning engineering projects end to end. Strong backend software engineering, Python, Bash, Linux, production systems, and data-processing experience are required, with GCP, Terraform, web crawling, and audio or ML dataset familiarity preferred.

Build scalable AI training-data pipelines, discover audio data sources, and optimize large-scale data processing for quality, throughput, and cost. Collaborate with AI scientists on datasets and models, operate production systems, and own engineering projects from discovery through continuous improvement. The role requires strong backend software engineering, Python and Bash proficiency in Linux environments, and independent problem-solving. Experience with crawlers, distributed processing, GCP, Terraform, and audio or ML data is advantageous.