Software Engineer, Data Infrastructure

About the job

Responsibilities

• Define Cartesia's multi-modal data strategy across pre-training and post-training, including human, synthetic, and web-scale sources, with a focus on audio.
• Design and operate scalable, high-throughput data pipelines for text, audio, and video, covering ingestion, preprocessing, augmentation, dataset versioning, and data loading for training.
• Collaborate with research and inference teams to co-design data systems with training and serving infrastructure.
• Establish and enforce rigorous data quality standards, linking dataset characteristics to model behavior.
• Identify and source novel datasets, managing relationships and budgets with external data vendors and partners.

Requirements

• Hands-on experience with ML data infrastructure, including training data pipelines, dataset versioning, large-scale data loading, and the interaction between data systems and model training/inference.
• Working knowledge of multimodal data, specifically audio formats, preprocessing, augmentation, and large-scale storage and streaming patterns.
• Strong modern engineering execution with clean, well-tested code and fluency with current tools.
• Experience leading cross-functional technical efforts in a fast-moving, research-driven environment.
• Familiarity with building and evaluating datasets for generative models and understanding of their training and inference processes.

Benefits

• Competitive base salary
• Attractive equity package
• Fully covered medical insurance, dental, and vision for employee and family
• 9 weeks paternity leave
• 12 weeks maternity leave
• 401(k)
• Monthly commuter allowance
• Flexible PTO
• Provided meals and snacks daily