AI Data Engineer - Large-Scale ML Data Pipelines

Speechify; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive compensation

Autonomy and async work culture

Impact in AI/Data domain

Job summary

Speechify is seeking a Software Engineer - AI Data to join its distributed AI team and build data pipelines powering model training. You will work with large-scale datasets, implement reliable data processing systems, and collaborate with AI scientists to improve training datasets and models.

The role emphasizes solving complex data problems, ownership of projects from discovery to delivery, and contributing to a product used by millions to learn more effectively.

Qualifications

• Degree in Computer Science or 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 with data pipelines or large-scale data processing.
• Strong problem-solving skills and ability to work independently in ambiguous environments.

Responsibilities

• Discover new sources of audio data and build pipelines to bring them into training datasets.
• Build and optimize large-scale data-processing systems for quality, throughput, and cost.
• Collaborate with AI scientists to improve training datasets and models.
• Own projects from problem discovery through implementation and continuous improvement.

Skills

5+ years of professional software eng.

Python

Bash

Data pipelines

Problem solving

Education

Bachelor's degree in Computer Science or related field

Tools

Linux

Job description

Speechify is seeking a Software Engineer - AI Data to join its distributed AI team and build data pipelines powering model training. You will work with large-scale datasets, implement reliable data processing systems, and collaborate with AI scientists to improve training datasets and models.

The role emphasizes solving complex data problems, ownership of projects from discovery to delivery, and contributing to a product used by millions to learn more effectively.