Top Tech Jobs & Startup Jobs in Boston, MA

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 training datasets and next-generation models while 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, optimizing 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, Python and Bash proficiency, production systems experience, and the ability to work independently 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, strong backend development, production systems experience, and proficiency in Python, Bash, and Linux. Preferred experience includes web crawling, distributed data processing, cloud infrastructure, Terraform, dataset quality, and audio processing.

Build large-scale audio data pipelines and processing systems that power 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. The role requires backend software engineering, production systems, and data-processing expertise, with preferred experience in web crawling, distributed systems, cloud infrastructure, Terraform, machine learning datasets, and audio processing.

Build and operate large-scale audio data pipelines for AI model training. Discover data sources, improve data processing systems, optimize 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 optimize large-scale audio data pipelines for AI model training. Discover data sources, develop production data-processing systems, improve dataset quality and throughput, and reduce costs. Collaborate with AI scientists and independently own engineering projects from discovery through continuous improvement. The role involves backend software engineering, distributed data processing, cloud infrastructure, and infrastructure as code.

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, production systems experience, and proficiency in Python, Bash, and Linux.

Build scalable data pipelines and processing systems for AI model training. 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 proficiency in Python, Bash, and Linux, with preferred experience in cloud infrastructure, Terraform, web crawling, distributed processing, and audio datasets.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, processing petabyte-scale datasets, 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. Responsibilities include discovering data sources, developing reliable processing systems, optimizing data 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.