AI Data Engineer: Build Scalable Datasets for Training

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

Descripción de la vacante

Speechify Inc. is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-gen AI products. We create high-quality datasets at scale by combining engineering, infrastructure, and research.

You will discover new data sources, build scalable pipelines, and collaborate with AI scientists to improve training datasets while owning projects end-to-end in a fully distributed environment.

Formación

• Degree in Computer Science or related field, 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 systems, with data pipelines or large-scale data processing.
• Strong problem-solving skills and 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

5+ years software eng

Python

Bash

Problem solving

Educación

Bachelor's degree in Computer Science or related field

Herramientas

GCP

Terraform

Data pipelines

Descripción del empleo

Speechify Inc. is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-gen AI products. We create high-quality datasets at scale by combining engineering, infrastructure, and research.

You will discover new data sources, build scalable pipelines, and collaborate with AI scientists to improve training datasets while owning projects end-to-end in a fully distributed environment.