Remote AI Data Engineer – Scale Training Pipelines

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

Benefits offered by this job

Autonomy

Asynchronous work culture

Competitive compensation

Impactful work

Job summary

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

You will design reliable ingestion from diverse audio sources, scale data processing, and collaborate with AI scientists to improve datasets and models, while enjoying a flexible remote environment and strong emphasis on asynchronous collaboration.

Qualifications

• Degree in Computer Science or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience with backend focus.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production data pipelines or large-scale data processing.
• Strong problem-solving skills and the ability to work independently in ambiguity.

Responsibilities

• Discover and ingest new audio data sources into training datasets.
• Build and optimize large-scale data-processing systems for quality and cost.
• Collaborate with AI Scientists to improve training datasets and models.
• Lead engineering projects from discovery to implementation and improvement.

Skills

Backend development

Python

Bash

Production systems

Data pipelines

Independent work

Problem solving

Education

Bachelor's degree in Computer Science or related field

Equivalent practical experience

Tools

GCP

Terraform

Job description

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

You will design reliable ingestion from diverse audio sources, scale data processing, and collaborate with AI scientists to improve datasets and models, while enjoying a flexible remote environment and strong emphasis on asynchronous collaboration.