Remote Software Engineer - AI Data Pipelines

Speechify; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Autonomy

Asynchronous work culture

Competitive compensation

Remote-first team

Job summary

Speechify is seeking a Software Engineer - AI Data to join its AI team and build data pipelines powering model training and next-generation AI products. The role focuses on creating high-quality datasets at petabyte scale by uniting engineering, infrastructure, and research.

You will own data pipelines end-to-end, collaborating with AI scientists to improve training data, data quality, throughput, and cost in a fast-moving, fully distributed environment.

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 reliable pipelines for training datasets.
• Build and improve large-scale data-processing systems, optimizing for quality, throughput, and cost.
• Collaborate with AI scientists to improve training datasets and models.
• Take ownership of engineering projects from discovery through implementation and improvement.

Skills

Backend development

Python

Bash

Linux

Data pipelines

Production systems

Problem solving

Independent work

Education

Bachelor's degree in Computer Science

Tools

GCP

Terraform

Job description

Speechify is seeking a Software Engineer - AI Data to join its AI team and build data pipelines powering model training and next-generation AI products. The role focuses on creating high-quality datasets at petabyte scale by uniting engineering, infrastructure, and research.

You will own data pipelines end-to-end, collaborating with AI scientists to improve training data, data quality, throughput, and cost in a fast-moving, fully distributed environment.