Remote AI Data Engineer — Scalable ML Data Pipelines

Speechify Inc.; Oregon; Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Autonomy

Asynchronous work culture

Competitive compensation

Impactful work

Job summary

Speechify Inc. is seeking a Software Engineer - AI Data to join the AI team and build data pipelines powering model training and next-generation AI products.

You will design high-quality data pipelines, participate in data acquisition, and work closely with AI scientists to improve training datasets and models. The role involves owning projects from problem discovery through implementation, with an emphasis on scalable systems, data quality, and cost efficiency in a distributed, fully remote

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

Python

Bash

Backend development

Problem solving

Education

Degree in Computer Science or related field

Job description

Speechify Inc. is seeking a Software Engineer - AI Data to join the AI team and build data pipelines powering model training and next-generation AI products.

You will design high-quality data pipelines, participate in data acquisition, and work closely with AI scientists to improve training datasets and models. The role involves owning projects from problem discovery through implementation, with an emphasis on scalable systems, data quality, and cost efficiency in a distributed, fully remote