Remote AI Data Engineer for Scalable Model Training

Speechify; Genf; Hybrid; CHF 25,000 - 132,000; Full time

Job summary

Speechify is seeking a Software Engineer - AI Data for its distributed team. You will build data pipelines powering model training and AI products, working with data sources and large-scale processing to improve training quality and efficiency.

You’ll collaborate with AI Scientists, own projects end-to-end, and contribute to a revolutionary reading technology used by millions, with a strong emphasis on asynchronous work culture and impact.

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 and ability to work independently in ambiguous environments.

Responsibilities

• Discover new sources of audio data and build reliable pipelines to bring them into training datasets.
• Build and improve large-scale data-processing systems, optimizing for data quality, throughput, and cost.
• Collaborate with AI Scientists to improve training datasets and support next-generation models.
• Take ownership of engineering projects from problem discovery through implementation and continuous improvement.

Skills

Backend development

Python

Bash

Problem solving

Independent work

Education

CS degree or equivalent

Tools

GCP

Terraform

Job description

Speechify is seeking a Software Engineer - AI Data for its distributed team. You will build data pipelines powering model training and AI products, working with data sources and large-scale processing to improve training quality and efficiency.

You’ll collaborate with AI Scientists, own projects end-to-end, and contribute to a revolutionary reading technology used by millions, with a strong emphasis on asynchronous work culture and impact.