Software Engineer - AI Data Pipelines

Speechify; United States; Remote; USD 140,000 - 190,000; Full time

Benefits offered by this job

Dynamic environment

Innovation valued

Autonomy

Significant impact

Competitive compensation

Job summary

Speechify is seeking a Software Engineer - AI Data to build data pipelines powering model training and next-generation AI products. You will discover new data sources, design reliable pipelines, and optimize data quality, throughput, and cost in a distributed, remote-friendly environment.

Work closely with AI scientists to improve training datasets, own projects from discovery to delivery, and help scale production data systems for petabyte-scale datasets.

Qualifications

• A degree in Computer Science or a related field, or equivalent practical experience.
• 5+ years of professional software engineering experience, with strong backend development 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

5+ years backend experience

Python

Bash

Data pipelines

Problem solving

Education

BS in Computer Science or related field

Job description

Speechify is seeking a Software Engineer - AI Data to build data pipelines powering model training and next-generation AI products. You will discover new data sources, design reliable pipelines, and optimize data quality, throughput, and cost in a distributed, remote-friendly environment.

Work closely with AI scientists to improve training datasets, own projects from discovery to delivery, and help scale production data systems for petabyte-scale datasets.