AI Data Engineer - Remote, Scale Data Pipelines

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

Benefits offered by this job

Asynchronous work culture

Competitive compensation

Equity

Job summary

Speechify Inc. is seeking a Software Engineer - AI Data to join our AI team. You will design and maintain data pipelines powering model training and next-generation AI products, handling petabyte-scale datasets with scalable systems.

You will collaborate with AI scientists, build reliable data-processing architectures, and own projects from conception to deployment. A strong backend foundation and experience with production data pipelines are essential.

Qualifications

• 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 ability to work independently in ambiguous environments.

Responsibilities

• Discover new sources of data and build reliable pipelines for training datasets.
• Build and improve large-scale data-processing systems focusing on quality, throughput, and cost.
• Collaborate with AI Scientists to enhance training datasets and models.
• Take ownership of projects from discovery through implementation and improvement.

Skills

Backend concepts

Problem solving

Independent work

Strong communication

Education

Degree in Computer Science or related field

Tools

Python

Bash

Linux environments

Data pipelines

Production systems

Job description

Speechify Inc. is seeking a Software Engineer - AI Data to join our AI team. You will design and maintain data pipelines powering model training and next-generation AI products, handling petabyte-scale datasets with scalable systems.

You will collaborate with AI scientists, build reliable data-processing architectures, and own projects from conception to deployment. A strong backend foundation and experience with production data pipelines are essential.