AI Data Engineer: Build Scalable ML Training Pipelines

Speechify; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Dynamic environment

Autonomy

Impact in industry

Competitive compensation

Asynchronous culture

Job summary

Speechify 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’ll discover new data sources, design scalable processing systems, and collaborate with AI scientists to enhance training datasets and model development. This role emphasizes data quality, efficiency, and cost optimization in a remote, fast-paced environment.

Qualifications

• 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.

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.

Skills

Backend development

Python

Bash

Data pipelines

Production systems

Education

Bachelor's degree in Computer Science

Tools

GCP

Terraform

Job description

Speechify 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’ll discover new data sources, design scalable processing systems, and collaborate with AI scientists to enhance training datasets and model development. This role emphasizes data quality, efficiency, and cost optimization in a remote, fast-paced environment.