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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. Speechify operates as a 100% distributed company with nearly 200 employees globally, including engineers from Amazon, Microsoft, Google, Stanford PhD programs, and high-growth startups like Stripe and Vercel.
You will join Speechify's AI team to build the data pipelines that power model training and next-generation AI products. The team focuses on creating high-quality datasets at petabyte scale while optimizing for cost, combining engineering, infrastructure, and research expertise.
Key responsibilities include:
- Discovering new sources of audio data and building reliable pipelines to integrate them into training datasets
- Building and improving large-scale data-processing systems, optimizing for data quality, throughput, and cost
- Collaborating closely with AI Scientists to enhance training datasets and support next-generation model development
- Taking ownership of engineering projects from problem discovery through implementation and continuous improvement
The role offers autonomy in a dynamic environment where your contributions directly shape the company and its products. You'll work at the intersection of artificial intelligence and audio technology, contributing to a product that changes lives for people 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
