AI Data Engineer - Build Scalable Training Pipelines

Speechify

United States

Remote

USD 140,000 - 200,000

Full time

2 days ago
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Benefits offered by this job

Autonomy
Impactful work
Asynchronous culture
Competitive compensation
Diverse workplace

Job summary

Speechify, a fully distributed AI-focused software company, seeks a Software Engineer - AI Data to build data pipelines powering model training and AI products. You will develop scalable data-processing systems and collaborate with AI scientists to improve datasets for next‑generation models.

The role emphasizes owning projects from discovery to deployment, solving complex data challenges, and contributing to an asynchronous, globally distributed team.

Qualifications

  • Degree in Computer Science or related field or equivalent practical experience.
  • 5+ years of professional software engineering experience.
  • 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 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.

Education

Bachelor's degree in Computer Science or related field
Equivalent practical experience

Tools

Python
Bash
Linux
GCP
Terraform

Job description

Speechify, a fully distributed AI-focused software company, seeks a Software Engineer - AI Data to build data pipelines powering model training and AI products. You will develop scalable data-processing systems and collaborate with AI scientists to improve datasets for next‑generation models.

The role emphasizes owning projects from discovery to deployment, solving complex data challenges, and contributing to an asynchronous, globally distributed team.

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