Research Engineer, Data Infrastructure (Language Modeling)

About the job

Responsibilities

• Build and operate scalable data processing infrastructure for acquiring, ingesting, and combining large text datasets.
• Design and operate scalable, high-throughput, and reproducible data pipelines for ingestion, preprocessing, filtering, deduplication, and augmentation.
• Design and conduct ablation experiments to analyze the impact of data sources, processing choices, and mixture weights on model quality.
• Collaborate with research and infrastructure teams to co-design data loading, versioning, and experimentation pipelines.
• Establish and enforce rigorous data quality standards with a feedback loop between dataset characteristics and 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, and large-scale data loading.
• Strong modern engineering skills with clean, well-tested code and fluency in current tools.
• Familiarity with building and evaluating datasets for generative models.
• Reasonable working knowledge of how generative models are trained and inferred.

Benefits

• Competitive base salary
• Attractive equity package
• Fully covered medical, dental, and vision insurance for employees and their families
• 9 weeks paternity leave
• 12 weeks maternity leave
• 401(k)
• Monthly commuter allowance
• Flexible PTO
• Provided meals and snacks
• Visa sponsorship support