Data Ingestion & Infra Engineer for AI Training Data

Speechify; Detroit (MI); Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive compensation

Equity

Asynchronous work culture

Impactful product helping learning

Job summary

Speechify is seeking a Software Engineer to join the Data side of our AI team. You will own data collection to support model training, building high-quality, scalable datasets at petabyte scale by tightly integrating infrastructure, engineering, and research work.

You will work with scientists to improve data cost, throughput, and quality while delivering data at scale to power next-generation products for both consumer and enterprise customers.

Qualifications

• BS/MS/PhD in Computer Science or related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments.
• Proficiency in Docker and Infrastructure-as-Code concepts and experience with at least one major Cloud Provider (GCP).
• Experience with web crawlers and large-scale data processing is a plus.
• Strong communication skills, both written and verbal.

Responsibilities

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline.
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently on GCP with Terraform.
• Collaborate with Scientists to optimize cost/throughput/quality for data at scale.
• Collaborate with the AI Team and Leadership to craft the dataset roadmap.

Skills

Software development

Bash scripting

Python scripting

Linux environments

Strong communication

Multi-tasking

Education

BS/MS/PhD in Computer Science

Tools

Docker

Terraform

GCP

Infrastructure as Code

Job description

Speechify is seeking a Software Engineer to join the Data side of our AI team. You will own data collection to support model training, building high-quality, scalable datasets at petabyte scale by tightly integrating infrastructure, engineering, and research work.

You will work with scientists to improve data cost, throughput, and quality while delivering data at scale to power next-generation products for both consumer and enterprise customers.