Remote AI Data Engineer - Scale ML Training Pipelines

Speechify Inc.; Polska; Hybrid; PLN 544,000 - 777,000; Full time

Job summary

Speechify Inc. is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-generation AI products.

You will work on petabyte-scale datasets, combining engineering, infrastructure, and research to improve data quality and efficiency. You will own projects from discovery to implementation, collaborating with AI scientists to advance models while operating in a distributed, remote-friendly environment that supports autonomous, high-impact

Qualifications

• 5+ years of professional software engineering experience.
• Strong backend development fundamentals.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production data pipelines or large-scale data processing.
• 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

Python

Bash

Data pipelines

Backend development

Problem-solving

Independent work

Education

Bachelor's degree in Computer Science

Tools

GCP

Terraform

Linux

Web crawlers

Distributed data-processing

Job description

Speechify Inc. is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-generation AI products.

You will work on petabyte-scale datasets, combining engineering, infrastructure, and research to improve data quality and efficiency. You will own projects from discovery to implementation, collaborating with AI scientists to advance models while operating in a distributed, remote-friendly environment that supports autonomous, high-impact