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About this role
Role overview A distributed software team focused on turning written content into spoken audio for tens of millions of users is hiring an engineer to own the data backbone of its machine learning operations. The role spans sourcing raw audio material, running petabyte-scale ingestion pipelines on cloud infrastructure, and partnering closely with researchers to feed ever-larger, higher-quality datasets into next-generation text-to-speech models. It's a hands-on engineering seat where infrastructure, scripting, and research priorities meet inside a fast-growing AI/audio product organization.
Responsibilities - Identify and onboard new audio data sources, integrating them into the existing ingestion workflow. - Operate, harden, and extend cloud-based ingestion infrastructure built with Infrastructure-as-Code tooling. - Work alongside applied scientists to push the cost, throughput, and quality frontier of training data. - Contribute to the dataset roadmap that powers upcoming consumer and enterprise product launches. - Build and maintain large-scale data processing pipelines that move petabytes efficiently and reliably.
Requirements - BS, MS, or PhD in Computer Science or a closely related discipline. - Five or more years of professional software engineering experience. - Strong proficiency with bash and Python scripting in Linux environments. - Solid grasp of Docker and Infrastructure-as-Code patterns, plus hands-on experience with at least one major cloud provider. - Comfort juggling multiple workstreams and adapting as priorities shift. - Clear written and verbal communication skills for cross-functional collaboration.
Nice to have - Experience designing or operating web crawlers and other large-scale data acquisition systems. - Familiarity with GCP and Terraform-managed environments.
Benefits and work setup - Fully distributed, remote-first culture with no central office. - Asynchronous workflows designed to minimize meetings and maximize deep work. - Entrepreneurial team culture that encourages initiative, intuition, and calculated risk-taking. - Hands-off management style that trusts engineers to own their work end-to-end. - Competitive compensation and a friendly, laid-back team atmosphere. - Opportunity to ship product used by millions, including accessibility features that support readers with dyslexia, ADHD, low vision, concussions, autism, and other learning differences. - Work at the intersection of artificial intelligence and consumer audio, one of the fastest-growing segments in tech.