Remote Research Engineer: Large-Scale ML Data Pipelines

UMAI Consultancy; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

ElevenLabs is seeking a Research Engineer to join the research team focused on the data infrastructure powering frontier AI models. You will own systems that enable high-quality, large-scale data for training state-of-the-art models.

You will thrive building data pipelines, training models within data processing workflows, and designing data curation strategies to measurably improve performance. The role emphasizes tooling and infrastructure to enable researchers to explore massive datasets

Qualifications

• Experience building data-intensive systems, ideally in support of ML training pipelines.
• Strong engineering skills in distributed data processing at scale (e.g., Kubernetes, or custom pipelines over large datasets).
• Ability to autonomously evaluate how data quality, composition, and curation affect model outcomes, and to build tooling to measure it.

Responsibilities

• Build large-scale data pipelines for collecting, processing, filtering, and transforming datasets for training state-of-the-art models.
• Train models used in data processing pipelines, such as classifiers, quality filters, and labeling models.
• Design data curation strategies like deduplication, quality scoring, labeling, and augmentation to improve model performance.
• Create tooling and infrastructure that lets researchers explore and train on massive datasets quickly and reliably.

Skills

Data-intensive systems

Distributed data processing

Data quality & curation

Tools

Kubernetes

Job description

ElevenLabs is seeking a Research Engineer to join the research team focused on the data infrastructure powering frontier AI models. You will own systems that enable high-quality, large-scale data for training state-of-the-art models.

You will thrive building data pipelines, training models within data processing workflows, and designing data curation strategies to measurably improve performance. The role emphasizes tooling and infrastructure to enable researchers to explore massive datasets