Remote AI Data Engineer to Build Large-Scale Pipelines

Speechify

United States

Remote

USD 120,000 - 170,000

Full time

2 days ago
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Benefits offered by this job

Competitive compensation
Autonomy and asynchronous work
Distributed, no-office culture
Impactful AI data initiatives
Welcoming team and growth

Job summary

Speechify is hiring a Software Engineer - AI Data to build data pipelines powering its AI models and datasets at petabyte scale. You will join a distributed team delivering high-quality data for model training and next-generation products.

The ideal candidate has 5+ years of software engineering experience with strong backend fundamentals, Python and Bash in Linux, and experience operating production data pipelines. This is a fully remote role with global impact.

Qualifications

  • 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 and large-scale data processing.

Responsibilities

  • Discover new sources of audio data and build pipelines for training datasets.
  • Build and optimize large-scale data-processing systems for quality, throughput, and cost.
  • Collaborate with AI Scientists to improve training datasets and model development.
  • Take ownership of projects from discovery through implementation and improvement.

Skills

Python
Bash
Backend development
Data pipelines
Linux

Education

Bachelor's degree in Computer Science or related field

Tools

GCP
Terraform

Job description

Speechify is hiring a Software Engineer - AI Data to build data pipelines powering its AI models and datasets at petabyte scale. You will join a distributed team delivering high-quality data for model training and next-generation products.

The ideal candidate has 5+ years of software engineering experience with strong backend fundamentals, Python and Bash in Linux, and experience operating production data pipelines. This is a fully remote role with global impact.

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