Data Infrastructure Engineer for Scalable AI Data Pipelines

Speechify; United States; On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive salary

Asynchronous culture

Impactful work

Global distributed team

Job summary

Speechify is hiring for its Data side of the AI team. This role focuses on data collection to support model training, building high-quality datasets at scale, and integrating infrastructure, engineering, and research to power next‑generation models.

You will source audio data, maintain ingestion pipelines on GCP with Terraform, and collaborate with scientists to optimize cost, throughput, and data quality while shaping the team’s dataset roadmap.

Qualifications

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments.
• Proficiency in Docker and IaC concepts with experience on at least one major cloud provider (GCP).
• Experience with web crawlers and large-scale data processing workflows is a plus.

Responsibilities

• Ingest and source new audio data into the ingestion pipeline.
• Operate and extend the cloud ingestion infrastructure on GCP using Terraform.
• Collaborate with AI Scientists to improve dataset cost, throughput, and quality.
• Help define the dataset roadmap with the AI Team and leadership.

Skills

5+ years software development

Bash / Python scripting

Docker

Terraform / IaC

GCP cloud experience

Web crawlers / data processing

Education

BS/MS/PhD in Computer Science or related field

Tools

Docker

Terraform

GCP

Linux

Python

Job description

Speechify is hiring for its Data side of the AI team. This role focuses on data collection to support model training, building high-quality datasets at scale, and integrating infrastructure, engineering, and research to power next‑generation models.

You will source audio data, maintain ingestion pipelines on GCP with Terraform, and collaborate with scientists to optimize cost, throughput, and data quality while shaping the team’s dataset roadmap.