AI Data Engineer: Scale Training Data Pipelines

Speechify Inc.; Oregon; Híbrido; USD 140.000 - 200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive compensation

Asynchronous work culture

Flexible schedule

Descripción de la vacante

Speechify is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-generation AI products. We craft high-quality datasets at petabyte scale, combining engineering, infrastructure, and research to improve training efficiency and scalability.

You will discover new audio data sources, build scalable data-processing systems, and collaborate with AI scientists to advance models.

Formación

• Degree in Computer Science or a related field, or equivalent practical experience.
• 5+ years of professional software engineering experience.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production systems, ideally involving data pipelines or large-scale data processing.
• Strong problem-solving skills and the ability to work independently in ambiguous environments.

Responsabilidades

• Discover new sources of audio data and build reliable pipelines to bring them into our training datasets.
• Build and improve large-scale data-processing systems, optimizing for data quality, throughput, and cost.
• Collaborate closely with AI Scientists to improve training datasets and support the development of next-generation models.
• Take ownership of engineering projects from problem discovery through implementation and continuous improvement.

Conocimientos

Backend development

Python

Bash

Production systems

Problem solving

Educación

Bachelor's degree in Computer Science or related field

Herramientas

GCP

Terraform

Descripción del empleo

Speechify is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-generation AI products. We craft high-quality datasets at petabyte scale, combining engineering, infrastructure, and research to improve training efficiency and scalability.

You will discover new audio data sources, build scalable data-processing systems, and collaborate with AI scientists to advance models.