Remote AI Data Engineer — Build Scalable ML Pipelines

Speechify; United States; Remote; USD 30,000 - 65,000; Full time

Benefits offered by this job

Competitive compensation

Asynchronous work culture

Autonomy in projects

Impactful work at scale

Job summary

Speechify is hiring a Software Engineer - AI Data to join our distributed AI team. You will design and maintain data pipelines powering model training and next-gen AI products, sourcing diverse audio data sources and building scalable data-processing systems.

You will collaborate with AI scientists to enhance datasets and models, take ownership from problem discovery to delivery, and work in a fast-paced, autonomous environment with strong emphasis on data quality and cost efficiency.

Qualifications

• Degree in Computer Science or a 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, especially data pipelines or large-scale data processing.

Responsibilities

• Discover new sources of audio data and build reliable pipelines for training datasets.
• Build and optimize large-scale data-processing systems for quality, throughput, and cost.
• Collaborate with AI Scientists to improve training datasets and models.
• Take ownership of engineering projects from discovery through implementation and improvement.

Skills

Python

Linux

Backend development

Data pipelines

Problem solving

Education

CS degree or equivalent

Tools

GCP

Terraform

Cloud infrastructure

Job description

Speechify is hiring a Software Engineer - AI Data to join our distributed AI team. You will design and maintain data pipelines powering model training and next-gen AI products, sourcing diverse audio data sources and building scalable data-processing systems.

You will collaborate with AI scientists to enhance datasets and models, take ownership from problem discovery to delivery, and work in a fast-paced, autonomous environment with strong emphasis on data quality and cost efficiency.