Top Tech Jobs & Startup Jobs in Boston, MA

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

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 emphasis on backend software development, production systems, and scalable data processing in a distributed environment.

Build and operate large-scale data pipelines for AI model training, including sourcing audio data, optimizing processing systems 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, Python, Bash, and Linux experience.

Build scalable data pipelines and processing systems for AI model training 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 while operating production systems in ambiguous environments.

Build and operate large-scale 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, Python and Bash proficiency, production systems experience, and independent problem-solving.

Build scalable, reliable pipelines for acquiring and processing audio data used in AI model training. The role involves optimizing large-scale data systems for quality, throughput, and cost; collaborating with AI scientists on training datasets; exploring data sources; and owning engineering projects from discovery through continuous improvement. Candidates should have strong backend software engineering experience, production systems expertise, and proficiency in Python and Bash.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering audio data sources, developing 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 processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role requires strong backend engineering, production systems experience, Python and Bash proficiency, and independent ownership of projects. Experience with web crawling, distributed processing, GCP, Terraform, machine-learning datasets, or audio processing is advantageous.

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. The role requires ownership of engineering projects from discovery through continuous improvement, with opportunities to work on web crawling, distributed processing, cloud infrastructure, infrastructure as code, dataset quality, and audio processing.

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. Strong backend software engineering, Python, Bash, Linux, and production systems experience are required, with GCP, Terraform, web crawling, and distributed processing experience preferred.