Top Artificial Intelligence Jobs

Build and operate large-scale pipelines for audio training data, discovering new data sources and optimizing processing for quality, throughput, and cost. Collaborate with AI scientists to improve datasets and support next-generation models. Own engineering projects from discovery through implementation and continuous improvement. The role requires strong backend software engineering, production systems experience, Python, Bash, and Linux proficiency, with cloud, Terraform, web crawling, and audio-processing experience beneficial.

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, 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 data-processing systems, optimizing data 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 scalable, reliable pipelines for acquiring and processing large-scale audio datasets used to train AI models. Improve data quality, throughput, and cost; collaborate with AI scientists; explore new data sources; and own 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 ingestion and processing systems, optimizing data 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 scalable data pipelines and processing systems for AI model training. The role involves discovering audio data sources, optimizing data quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. Candidates should have strong backend software engineering experience, production systems expertise, and proficiency in Python, Bash, and Linux. Experience with web crawlers, distributed processing, cloud infrastructure, Terraform, ML datasets, or audio processing is advantageous.

Build and operate large-scale data pipelines that collect audio data for AI training. Responsibilities include 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 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, production systems, and independent problem-solving skills.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, optimizing data processing 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, optimizing processing systems for quality, throughput, and cost, and collaborating with AI scientists. Own 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. Experience with web crawling, distributed processing, GCP, Terraform, and audio or ML datasets is beneficial.

Build scalable data pipelines and processing systems for AI model training. Responsibilities include discovering audio data sources, improving dataset quality and processing efficiency, operating production systems, and collaborating with AI scientists. The role requires strong backend software engineering skills, Python and Bash proficiency, and the ability to independently own projects from discovery through continuous improvement.

Build scalable AI training data pipelines, discover and acquire audio data, optimize large-scale data processing for quality, throughput, and cost, and collaborate with AI scientists on next-generation models. The role requires production backend engineering, independent project ownership, and experience with data pipelines or distributed processing. Preferred experience includes web crawling, cloud infrastructure, Terraform, machine-learning datasets, and audio processing.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, processing datasets at petabyte scale, optimizing quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

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

Build scalable pipelines and data-processing systems for AI model training. Responsibilities include discovering audio data sources, improving dataset quality, optimizing 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 with Python, Bash, and Linux. Experience with web crawlers, distributed processing, GCP, Terraform, and audio or ML training data is advantageous.

Build scalable data pipelines and processing systems for AI model training. Responsibilities include discovering audio data sources, optimizing dataset quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build scalable, reliable pipelines for acquiring and processing large-scale audio datasets used in AI model training. Improve data quality, throughput, and cost while collaborating with AI scientists on next-generation models. Own engineering projects from discovery through implementation and continuous improvement, using backend development, production systems, and data-processing expertise.

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.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, improving data processing systems, and optimizing data 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 proficiency in Python, Bash, and Linux.

Build scalable AI training-data pipelines and large-scale data-processing systems for high-quality audio 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. 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. Discover data sources, improve data-processing systems, and optimize dataset quality, throughput, and cost. Collaborate with AI scientists on next-generation models and own engineering projects from discovery 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 data pipelines that source, process, and improve audio datasets for AI model training. The role involves optimizing data quality, throughput, and cost; collaborating with AI scientists; exploring new data sources; and owning engineering projects from discovery through continuous improvement. Candidates need strong backend software engineering experience, Python and Bash proficiency, production systems experience, and the ability to work independently in ambiguous environments.

Build scalable data pipelines and processing systems for AI training datasets at petabyte scale. 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 in a distributed environment.

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 on next-generation models. Responsibilities include owning engineering projects from discovery through continuous improvement. Required experience includes backend software engineering, production systems, Python, Bash, and Linux; cloud infrastructure, Terraform, web crawling, and distributed processing are advantageous.