AI Data Engineer: Scale Training Pipelines

Speechify; United States; A distancia; USD 140.000 - 200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Autonomy

Innovation

Competitive pay

Asynchronous work culture

Career growth

Descripción de la vacante

Speechify is seeking a Software Engineer - AI Data to join its AI team and build robust data pipelines powering model training and next-generation products. You will help collect and curate high-quality audio datasets, design scalable pipelines, and work with AI scientists to improve data for training.

In a fully remote, distributed environment, you will own projects from discovery to deployment, applying Python and Bash on Linux, and leveraging cloud infrastructure such as GCP and Terraform to

Formación

• Degree in Computer Science or equivalent practical experience.
• 5+ years of professional software engineering experience with backend focus.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production data pipelines or large-scale data processing.
• Strong problem-solving, initiative, and ability to work independently in ambiguous environments.

Responsabilidades

• Discover new data sources and build pipelines for training datasets.
• Build and improve large-scale data-processing systems for quality and cost.
• Collaborate with AI Scientists to improve training datasets and models.
• Own projects from discovery to implementation and improvement.

Conocimientos

Python

Bash

Backend development

Data pipelines

Linux

Educación

Computer Science degree

Herramientas

Terraform

GCP

Descripción del empleo

Speechify is seeking a Software Engineer - AI Data to join its AI team and build robust data pipelines powering model training and next-generation products. You will help collect and curate high-quality audio datasets, design scalable pipelines, and work with AI scientists to improve data for training.

In a fully remote, distributed environment, you will own projects from discovery to deployment, applying Python and Bash on Linux, and leveraging cloud infrastructure such as GCP and Terraform to