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Salary: USD 30,000 - 120,000 / 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 has ~200 employees globally in a fully distributed setting, with team members from Amazon, Microsoft, Google, Stanford, and other leading organizations.
You'll join the AI team as a Software Engineer focused on AI Data, responsible for building and maintaining the data pipelines that power Speechify's model training and next-generation AI products. The role involves discovering new audio data sources, building reliable ingestion pipelines, and optimizing large-scale data-processing systems for quality, throughput, and cost efficiency.
Key responsibilities include:
- Discovering and integrating new audio data sources into training datasets
- Building and improving large-scale data-processing systems with focus on quality, throughput, and cost optimization
- Collaborating with AI Scientists to enhance training datasets and support next-generation model development
- Owning engineering projects end-to-end from problem discovery through implementation and continuous improvement
The role offers autonomy in a dynamic environment where your contributions directly shape the product. You'll work on the intersection of AI and audio technology, contributing to a product that particularly impacts users with learning differences like dyslexia and ADD.
**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
