Senior AI Data Pipeline Engineer

Speechify; United States; Remoto; USD 30.000 - 120.000; Tempo pieno

Vantaggi offerti da questo lavoro

Autonomy

Asynchronous work culture

Competitive compensation

Stock options

Impactful AI work

Descrizione del lavoro

Speechify is seeking a Software Engineer - AI Data to join its AI team and build data pipelines powering model training and next-generation AI products. You will develop and operate large-scale data-processing systems and collaborate with AI scientists to improve training datasets.

Ideal candidates have 5+ years in software engineering, strong back-end skills in Python and Bash, and experience with production data pipelines.

Competenze

• Bachelor's level or above with strong software engineering background.
• 5+ years of professional software engineering experience, backend-focused.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production systems, especially data pipelines or large-scale data processing.
• Strong problem-solving skills and ability to work independently in ambiguous environments.

Mansioni

• 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 model development.
• Take ownership of projects from discovery through implementation and continuous improvement.

Conoscenze

Python

Bash

Data pipelines

Backend development

Linux

Formazione

CS degree or related field

Strumenti

GCP

Terraform

Airflow

Descrizione del lavoro

Speechify is seeking a Software Engineer - AI Data to join its AI team and build data pipelines powering model training and next-generation AI products. You will develop and operate large-scale data-processing systems and collaborate with AI scientists to improve training datasets.

Ideal candidates have 5+ years in software engineering, strong back-end skills in Python and Bash, and experience with production data pipelines.