Remote AI Data Engineer - Scale & Innovate ML Pipelines

Speechify Inc.; Polska; Ibrido; PLN 117.000 - 428.000; Tempo pieno

Vantaggi offerti da questo lavoro

Autonomy

Asynchronous work

Descrizione del lavoro

Speechify is a 100% distributed company seeking a Software Engineer - AI Data to join the AI team and build data pipelines powering model training and next-gen AI products. We develop high-quality datasets at petabyte scale and cost-efficiently, combining engineering, infrastructure, and research to advance AI training.

Ideal candidates enjoy solving complex problems, exploring new data sources, and building scalable systems.

Competenze

• Degree in Computer Science or 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 and the ability to work independently in ambiguous environments.

Mansioni

• 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.

Conoscenze

Python programming

Bash scripting

Linux environments

Data pipelines

Backend development

Problem solving

Formazione

Bachelor's degree in Computer Science or related field

Strumenti

GCP

Terraform

Descrizione del lavoro

Speechify is a 100% distributed company seeking a Software Engineer - AI Data to join the AI team and build data pipelines powering model training and next-gen AI products. We develop high-quality datasets at petabyte scale and cost-efficiently, combining engineering, infrastructure, and research to advance AI training.

Ideal candidates enjoy solving complex problems, exploring new data sources, and building scalable systems.