Software Engineer, AI Data - Build Scalable ML Data Pipelines

Speechify; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Fully distributed with no office

Autonomy to focus and create

Impactful work in AI data space

Asynchronous-friendly work culture

Job summary

Speechify is seeking a Software Engineer - AI Data to join our distributed AI team. You will build data pipelines powering model training and next-generation AI products, handling petabyte-scale datasets with cost efficiency.

You’ll collaborate with AI Scientists to improve training datasets and models, own engineering projects end-to-end, and help expand our data infrastructure across cloud and on-prem capabilities in a fast-moving, async-friendly environment.

Qualifications

• Degree in Computer Science or related field, or equivalent practical experience.
• 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 or large-scale data processing.
• Strong problem-solving, initiative, and ability to work independently in ambiguous environments.

Responsibilities

• Discover new data sources and build pipelines to ingest them into training datasets.
• Develop and optimize large-scale data-processing systems for quality, throughput, and cost.
• Collaborate with AI Scientists to improve training data and model development.
• Own projects from discovery through implementation and ongoing improvement.

Skills

Python

Bash

Linux

Data pipelines

Backend development

Education

Bachelor's degree in Computer Science or related field

Tools

GCP

Terraform

Job description

Speechify is seeking a Software Engineer - AI Data to join our distributed AI team. You will build data pipelines powering model training and next-generation AI products, handling petabyte-scale datasets with cost efficiency.

You’ll collaborate with AI Scientists to improve training datasets and models, own engineering projects end-to-end, and help expand our data infrastructure across cloud and on-prem capabilities in a fast-moving, async-friendly environment.