Top Artificial Intelligence Jobs

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 through continuous improvement. The role requires strong backend software engineering, production systems experience, Python and Bash proficiency, and the ability to work independently in an ambiguous environment.

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. Responsibilities include discovering data sources, developing reliable processing systems, 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 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 audio data pipelines for AI model training. The role involves discovering data sources, developing high-throughput processing systems, optimizing dataset quality and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The engineer will work with Python, Bash, Linux, cloud infrastructure, and potentially distributed processing, web crawling, data acquisition, Terraform, and audio processing.

Build and operate large-scale data pipelines that collect, process, and optimize audio datasets for AI model training. The role involves discovering new data sources, improving data quality, throughput, and cost efficiency, 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 data sources, improve processing systems for quality, throughput, and cost, and collaborate with AI scientists on next-generation models. 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 data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects through continuous improvement.

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, Python, Bash, and Linux proficiency.

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, 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 data sources, improve 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 for AI model training. Responsibilities include discovering data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement in a distributed, autonomous environment.

Build and operate large-scale audio data pipelines 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 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 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 a focus on production systems, scalable data processing, and efficient dataset development.

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 large-scale data pipelines and processing systems for AI model training. Discover audio 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. The role requires strong backend software engineering, production systems experience, and proficiency with Python, Bash, and Linux. Experience with web crawlers, distributed processing, cloud infrastructure, Terraform, and audio or ML datasets 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, 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 petabyte-scale audio data pipelines for AI model training. The role involves 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 scalable data pipelines and large-scale processing systems for AI model training datasets. Discover audio data sources, optimize data quality, throughput, and cost, and collaborate with AI scientists on next-generation models. The role requires ownership of engineering projects from discovery through continuous improvement in a distributed, autonomous environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering audio data sources, developing data-processing systems, optimizing 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. 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 AI training-data pipelines and large-scale data-processing systems. Discover and acquire audio data, optimize data quality, throughput, and cost, and collaborate with AI scientists on next-generation models. Own engineering projects from discovery through continuous improvement in a distributed environment.

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, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.