Research Engineer, AI Data Infrastructure & Datasets

Cartesia; San Francisco (CA); On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

Compensation

Health Insurance

Parental Leave

401(k)

Commuter Allowance

Flexible PTO

Meals & Snacks

Your own personal Yoshi

Job summary

Cartesia is seeking a Research Engineer, Data Infrastructure to build the datasets and systems powering pretraining. You will write scalable infrastructure to acquire, process, and curate massive datasets, partnering with research to optimize data mixtures.

Your work will shape the capabilities and quality of our foundational models. In this in-person role, you will join an interdisciplinary team based in SF and work closely with researchers and infrastructure engineers to design data loading,

Qualifications

• Experience building ML data infrastructure and datasets for large-scale models.
• Proficiency with data pipelines, versioning, and scalable loading.
• Ability to collaborate with researchers and infrastructure teams.

Responsibilities

• Build scalable data processing infrastructure for acquiring, ingesting, and combining massive text datasets.
• Design and run high-throughput, reproducible data pipelines for ingestion, preprocessing, filtering, deduplication and augmentation.
• Design ablation experiments to understand how data sources and weights affect model quality.
• Partner with research and infra teams to co-design data loading, versioning, and experimentation pipelines.
• Establish and enforce data quality standards with tight feedback between datasets and model behavior.
• Identify and source novel datasets and manage relationships with external data vendors.

Skills

Data pipelines

Dataset versioning

Large-scale data loading

Python/Scala

Collaborative research

Tools

Ray

Spark

Kubernetes

Job description

Cartesia is seeking a Research Engineer, Data Infrastructure to build the datasets and systems powering pretraining. You will write scalable infrastructure to acquire, process, and curate massive datasets, partnering with research to optimize data mixtures.

Your work will shape the capabilities and quality of our foundational models. In this in-person role, you will join an interdisciplinary team based in SF and work closely with researchers and infrastructure engineers to design data loading,