Software Engineer, AI Data
Speechify · Remote · remote · Posted 9d ago
Undisclosed5–10 yrsfulltimeSourced from
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About this role
Job Summary
Overview
What You'll Do:
An Ideal Candidate Should Have:
Nice to Have
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
The mission of Speechify is to make sure that reading is never a barrier to learning.
Over 50 million people use Speechifys text-to-speech products to turn whatever theyre reading - PDFs, books, Google Docs, news articles, websites - into audio, so they can read faster, read more, and remember more. Speechifys text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its Design Award winner for Inclusivity.
Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting - Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google,
leading PhD programs like Stanford, high-growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.
leading PhD programs like Stanford, high-growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.
Overview
Were looking for a Software Engineer - AI Data to join Speechifys AI team and build the data pipelines that power our model training and next-generation AI products.
We build high-quality datasets at petabyte scale and low cost by combining engineering, infrastructure, and research. Were looking for a strong software engineer who enjoys solving complex problems, exploring new data sources, and building systems that make AI training more efficient and scalable.
What You'll Do:
- Discover new sources of audio data and build reliable pipelines to bring them into our training datasets.
- Build and improve large-scale data-processing systems, optimizing for data quality, throughput, and cost.
- Collaborate closely with AI Scientists to improve training datasets and support the development of next-generation models.
- Take ownership of engineering projects from problem discovery through implementation and continuous improvement.
An Ideal Candidate Should Have:
- A degree in Computer Science or a 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 the 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.
Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Skills
data qualityBashdata acquisitiongoogle cloud platformEngineering projectsAi ResearchAI TrainingAsynchronousAudio ProcessingCloud InfrastructureAndroidcloudData ProcessingBackend DevelopmentData PipelineArtificial Intelligence
About Speechify
Speechify
IT Services & Consulting
51-200
employees
2017
9 years old
Miami
CO
About
Speechify develops a text-to-speech application aimed at improving information accessibility, particularly for individuals with learning differences in the tech industry.
Industries
IT Services & Consulting
Employee ratings
4 reviews
2.3/ 5
Culture
2.8
Career growth
2.0
Work-life
3.3
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