Software Engineer, AI Data

Role overview Build the data pipelines and processing systems that supply audio datasets for AI model training. The work spans data sourcing, backend engineering, and collaboration with research teams to make training data more reliable, scalable, and cost-effective.

Responsibilities - Find audio data sources and develop dependable pipelines to collect and incorporate data into training datasets. - Build and improve large-scale processing systems, balancing data quality, throughput, and operating cost. - Work with AI researchers to improve datasets and support development of new models. - Lead engineering work from identifying a problem through implementation and ongoing refinement.

Requirements - A degree in computer science or a related discipline, or equivalent practical experience. - At least five years of software engineering experience and solid backend fundamentals. - Proficiency in Python and Bash in Linux environments. - Experience building and operating production systems; data pipelines or large-scale processing are especially relevant. - Strong problem-solving skills, initiative, and the ability to work independently amid ambiguity.

Nice to have - Experience with web crawlers, data acquisition, or distributed processing. - Familiarity with cloud infrastructure and infrastructure as code, particularly GCP and Terraform. - Knowledge of machine-learning datasets, data quality, or audio processing.

Benefits and work setup The role offers autonomy and an asynchronous work culture, with the opportunity to influence products and work at the intersection of AI and audio. For US-based candidates, listed base pay is USD 140,000–200,000, plus bonus and equity, depending on experience.