Senior Data Infrastructure Engineer – AI Data Acquisition

Speechify; Fremont (CA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Competitive salaries

Remote/distributed work

Impactful AI/audio product

Equity participation

Job summary

Speechify is hiring a Software Engineer for the Data/AI team to own data collection and ingestion pipelines that support large-scale model training. You will help build petabyte-scale datasets by closely integrating infrastructure, engineering, and research work.

You’ll collaborate with scientists to improve throughput, cost, and quality, extend cloud infrastructure on GCP, and contribute to next-generation consumer and enterprise AI products in a distributed, fully remote team.

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.

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 running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

Skills

bash/Python scripting

Docker

Infrastructure as Code

GCP

Web crawlers

Data processing workflows

Multitasking

Communication skills

Education

BS/MS/PhD in Computer Science or related field

Job description

Speechify is hiring a Software Engineer for the Data/AI team to own data collection and ingestion pipelines that support large-scale model training. You will help build petabyte-scale datasets by closely integrating infrastructure, engineering, and research work.

You’ll collaborate with scientists to improve throughput, cost, and quality, extend cloud infrastructure on GCP, and contribute to next-generation consumer and enterprise AI products in a distributed, fully remote team.