Senior Software Engineer, AI Data Pipelines

Speechify; United States; Teletrabalho; USD 140 000 - 200 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive compensation

Asynchronous culture

Autonomy

Impact in AI

Resumo da oferta

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

We build high-quality datasets at petabyte scale and require a strong software engineer who enjoys solving complex problems, exploring new data sources, and building systems that make AI training more efficient and scalable.

Qualificações

• Degree in Computer Science or 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, ideally with data pipelines or large-scale processing.
• Strong problem-solving, initiative, and ability to work independently in ambiguous environments.

Responsabilidades

• Discover new sources of audio data and build reliable pipelines to bring them into 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 next-generation models.
• Take ownership of engineering projects from problem discovery through implementation and continuous improvement.

Conhecimentos

Backend development

Python

Bash

Problem solving

Formação académica

Bachelor's degree in Computer Science or related field

Ferramentas

GCP

Terraform

Linux

Descrição da oferta de emprego

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

We build high-quality datasets at petabyte scale and require a strong software engineer who enjoys solving complex problems, exploring new data sources, and building systems that make AI training more efficient and scalable.