Top Tech Jobs & Startup Jobs in Chicago, IL

Build scalable pipelines and data-processing systems for AI training datasets at petabyte scale. 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, production systems experience, and proficiency in Python, Bash, and Linux, with preferred experience in data acquisition, distributed processing, cloud infrastructure, Terraform, machine learning data, or audio processing.

Build scalable pipelines for acquiring, processing, and curating audio data used in AI model training. Improve data quality, throughput, and cost at petabyte scale; collaborate with AI scientists on datasets and next-generation models; 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, 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 that acquire, 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.

Build and operate large-scale data pipelines that acquire, process, and improve audio datasets for AI model training. The role focuses on data quality, throughput, cost optimization, production systems, and collaboration with AI scientists. Responsibilities include discovering data sources, developing reliable processing systems, 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 acquisition and processing systems, optimizing dataset quality, throughput, and cost, and collaborating with AI scientists. The role owns engineering projects end to end and may involve web crawling, distributed processing, cloud infrastructure, Infrastructure as Code, and audio dataset quality.

Build and operate large-scale data pipelines supporting AI model training and next-generation products. Responsibilities include discovering audio data sources, developing reliable data acquisition and 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 software engineering, production systems, and scalable data processing.

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, 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, collaborate with AI scientists, and 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, with cloud infrastructure and Terraform experience preferred.

Build and optimize petabyte-scale data pipelines for AI model training, including audio data acquisition, large-scale processing, and dataset quality improvements. Collaborate with AI scientists, operate production systems, and independently manage engineering projects from discovery through continuous improvement. The role emphasizes backend software engineering, scalability, throughput, cost efficiency, and reliable infrastructure.