Top Artificial Intelligence Jobs

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The engineer will own projects from discovery through implementation and ongoing improvement, using strong backend engineering skills in Python, Bash, and Linux environments.

Build scalable data pipelines and processing systems for AI model training datasets. Responsibilities include discovering audio 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 for AI model training, including discovering audio data sources, processing datasets, and optimizing quality, throughput, and cost. Collaborate with AI scientists on training data 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 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 AI training data pipelines, discover audio data sources, optimize data processing for quality, throughput, and cost, and collaborate with AI scientists on next-generation models. The role owns engineering projects from discovery through implementation and continuous improvement in a fully distributed environment.

Build and operate large-scale audio data pipelines for AI model training. Discover data sources, optimize 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, autonomous environment.

Build and operate large-scale audio data pipelines that support 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 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 data pipelines for AI training datasets, including discovering audio data sources, optimizing processing systems for quality, throughput, and cost, and collaborating 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 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 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 petabyte-scale data pipelines for AI model training, including sourcing audio data, improving processing systems, optimizing 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 development, production systems, and scalable data processing.

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.

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 and operate petabyte-scale audio data pipelines for AI model training. The role involves discovering data sources, improving large-scale processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The engineer will own projects from discovery through implementation and continuous improvement, using Python, Bash, Linux, cloud infrastructure, and potentially GCP and Terraform.

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, 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, improving data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. Candidates need strong backend software engineering experience, Python and Bash proficiency in Linux environments, and experience operating production systems and data pipelines.

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 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 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 for AI model training. Discover data sources, optimize 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, asynchronous environment.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, optimizing 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 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 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 experience, Python and Bash proficiency, production systems expertise, and the ability to work independently in ambiguous environments.