AI Data Engineer - Scalable Data Pipelines (Remote)

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

Benefits offered by this job

Autonomy

Asynchronous culture

Remote-first environment

Competitive compensation

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.

We develop high-quality datasets at petabyte scale, blending engineering, infrastructure, and research to improve training efficiency and scalability. You will solve complex problems, explore new data sources, and own engineering projects from discovery to delivery in a distributed, remote-friendly environment.

Qualifications

• Degree in Computer Science or 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 with data pipelines or large-scale data processing.
• Strong problem-solving skills and the 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

Backend development

Data pipelines

Problem-solving

Education

Degree in Computer Science or related field

Tools

GCP

Terraform

Linux

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.

We develop high-quality datasets at petabyte scale, blending engineering, infrastructure, and research to improve training efficiency and scalability. You will solve complex problems, explore new data sources, and own engineering projects from discovery to delivery in a distributed, remote-friendly environment.