AI Data Engineer for Scalable ML Pipelines

Speechify; United States; Remote; USD 140.000 - 200.000; Vollzeit

Benefits dieser Stelle

Dynamic environment

Innovative team

Autonomy

Impact in AI & audio

Competitive compensation & async work

Dyslexia-friendly product impact

AI & audio domain

Zusammenfassung

Speechify is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-generation AI products. We create high-quality, petabyte-scale datasets and seek engineers who enjoy solving complex data problems and building scalable systems.

You’ll discover data sources, optimize pipelines for quality and cost, and collaborate with AI scientists to improve training data.

Qualifikationen

• Degree in Computer Science or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience with backend fundamentals.
• Proficiency in Python and Bash in Linux environments.
• Experience building and operating production data pipelines or large-scale data processing.
• Strong problem-solving, initiative, and ability to work independently in ambiguous environments.

Aufgaben

• 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.

Jobbeschreibung

Speechify is seeking a Software Engineer - AI Data to join our AI team and build data pipelines powering model training and next-generation AI products. We create high-quality, petabyte-scale datasets and seek engineers who enjoy solving complex data problems and building scalable systems.

You’ll discover data sources, optimize pipelines for quality and cost, and collaborate with AI scientists to improve training data.