Cartesia
Research Engineer, Data Infrastructure (Language Modeling)
$200K–$350K
*HQ - San Francisco, CA · On-site · Full-time · Posted Sep 24, 2026
- Visa sponsorship
- Visa sponsorship support is provided and assessed case by case; availability depends on the role and work location and is not guaranteed.
About the job
Builds data infrastructure and datasets for language-model pretraining, shaping data mixtures and evaluating their effects on model quality.
What you'll do
- Build and operate scalable infrastructure and reproducible pipelines to acquire, process, and curate large text datasets.
- Run ablation experiments and partner with research and infrastructure teams on data quality, loading, versioning, and experimentation.
- Source datasets and manage relationships and budgets with external data vendors and partners.
What they ask for
- Hands-on experience with ML data infrastructure, including training data pipelines, dataset versioning, and large-scale data loading.
- Strong modern engineering execution, including clean, well-tested code and selecting appropriate tools.
- Familiarity with building and evaluating generative-model datasets and working knowledge of model training and inference.
Nice to have
- Experience with large-scale data processing using parallel infrastructure such as Ray, Spark, or Kubernetes.
- Experience with pretraining language models.
Pay
$200K – $350K USD base salary
Tools
Ray, Spark, Kubernetes
AI focus
Supports language-model pretraining by building datasets and data systems and studying how data choices affect foundational-model quality.
Model-written summary · the original posting is authoritative