AI Data Engineer: Large-Scale ML Data Pipelines

Speechify Inc.; Oregon; Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Autonomy

Competitive compensation

Asynchronous work culture

Job summary

Speechify is seeking a Software Engineer - AI Data to join its distributed AI team and build data pipelines powering model training and future AI products. You’ll help create high-quality datasets at scale, combining engineering, infrastructure, and research to drive efficiency and scalability.

You will discover new data sources, develop large-scale data-processing systems, and collaborate with AI Scientists to enhance training data and models.

Qualifications

• A degree in Computer Science or a related field, or equivalent practical experience.
• 5+ years of professional software engineering experience with strong backend development fundamentals.
• 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, initiative, and the ability to work independently in ambiguous environments.

Responsibilities

• 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.

Skills

Backend development

Python

Bash

Production systems

Data pipelines

Problem-solving

Independent work

Education

Bachelor's degree in Computer Science or related field

Tools

GCP

Terraform

Job description

Speechify is seeking a Software Engineer - AI Data to join its distributed AI team and build data pipelines powering model training and future AI products. You’ll help create high-quality datasets at scale, combining engineering, infrastructure, and research to drive efficiency and scalability.

You will discover new data sources, develop large-scale data-processing systems, and collaborate with AI Scientists to enhance training data and models.