Senior AI Data Engineer: Build Scalable Training Pipelines

Speechify; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive compensation

Asynchronous work culture

Impactful work in AI/Audio

Job summary

Speechify is hiring a Software Engineer - AI Data to join its AI team and build data pipelines powering model training and next-generation AI products. Work spans acquiring data sources, creating scalable data-processing systems, and collaborating with AI scientists to improve training datasets and models.

The role emphasizes ownership of projects from discovery to delivery in a distributed, office-free environment with a strong focus on data quality and cost efficiency.

Qualifications

• Degree in Computer Science or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience with 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.
• Strong problem-solving skills, initiative, and the 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.

Skills

Python

Bash

Linux

Data pipelines

Production systems

Education

B.S. in Computer Science

Tools

GCP

Terraform

Job description

Speechify is hiring a Software Engineer - AI Data to join its AI team and build data pipelines powering model training and next-generation AI products. Work spans acquiring data sources, creating scalable data-processing systems, and collaborating with AI scientists to improve training datasets and models.

The role emphasizes ownership of projects from discovery to delivery in a distributed, office-free environment with a strong focus on data quality and cost efficiency.