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Salary: USD 140,000 - 200,000 / 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 recently 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 focused on making reading accessible to all learners.
You will join Speechify's AI team as a Software Engineer focused on AI Data, responsible for building the data pipelines that power model training and next-generation AI products. The role involves discovering new sources of audio data and constructing reliable pipelines to integrate them into training datasets. You'll build and improve large-scale data-processing systems optimized for data quality, throughput, and cost efficiency. Close collaboration with AI Scientists will be essential to enhance training datasets and support the development of advanced models. You'll take full ownership of engineering projects from problem discovery through implementation and continuous improvement.
Key responsibilities include: discovering and sourcing new audio data; building and optimizing production-scale data-processing systems; collaborating with AI researchers to improve dataset quality; and owning projects end-to-end in a distributed, autonomous environment.
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 (GCP, Terraform)
- Familiarity with ML training data, dataset quality, or audio processing
