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Salary: USD 30,000 - 100,000 / annual
Speechify is a text-to-speech platform used by over 50 million people to convert PDFs, books, Google Docs, news articles, and websites into audio. The company was named Chrome Extension of the Year by Google and received Apple's 2025 Design Award for Inclusivity. With ~200 employees globally in a fully distributed setting, Speechify is building next-generation AI products for accessibility.
You will join the AI team as a Software Engineer focused on AI Data, responsible for building and maintaining the data pipelines that power model training and next-generation AI products. The team works at petabyte scale, combining engineering, infrastructure, and research to create high-quality datasets efficiently and cost-effectively.
Key responsibilities:
- Discover new sources of audio data and build reliable pipelines to integrate 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 enhance training datasets and support development of next-generation models
- Own engineering projects from problem discovery through implementation and continuous improvement
You will work independently in a distributed environment, taking initiative on complex problems and exploring novel data sources. The role requires strong backend engineering fundamentals and the ability to operate production systems at scale.
**Requirements:**
- Bachelor's degree in Computer Science or related field, or equivalent practical experience
- 5+ years of professional software engineering experience with strong backend development fundamentals
- Proficiency in Python and Bash in Linux environments
- Experience building and operating production systems, ideally involving data pipelines or large-scale data processing
- Strong problem-solving skills, initiative, and ability to work independently in ambiguous environments
**Nice to have:**
- Experience with web crawlers, data acquisition, or distributed data-processing systems
- Experience with cloud infrastructure and Infrastructure as Code, particularly GCP and Terraform
- Familiarity with ML training data, dataset quality, or audio processing
