Remote AI Data Engineer — Scale ML Data Pipelines

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

Benefits offered by this job

Competitive compensation

Autonomy

Asynchronous work environment

Impactful work

Job summary

Speechify is seeking a Software Engineer - AI Data to build data pipelines powering model training and AI products. You will work on petabyte-scale datasets, optimizing for quality, throughput, and cost while collaborating with AI scientists to improve training data.

The role emphasizes independent problem solving, ownership of projects from discovery to delivery, and building robust data systems in a distributed, async-friendly environment.

Qualifications

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

Responsibilities

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

Skills

Backend development

Python

Bash

Linux environments

Data pipelines

Production systems

Problem solving

Independent work

Education

Computer Science or related field

Tools

Terraform

Google Cloud Platform (GCP)

Job description

Speechify is seeking a Software Engineer - AI Data to build data pipelines powering model training and AI products. You will work on petabyte-scale datasets, optimizing for quality, throughput, and cost while collaborating with AI scientists to improve training data.

The role emphasizes independent problem solving, ownership of projects from discovery to delivery, and building robust data systems in a distributed, async-friendly environment.