Note: The job is a remote job and is open to candidates in USA. ElevenLabs is hiring a Research Engineer to build and own data infrastructure for its frontier AI models. The role focuses on scalable data pipelines, models and strategies for data curation, and tools that help researchers explore and train on large datasets.

Responsibilities

• Building large-scale data pipelines for collecting, processing, filtering, and transforming datasets used to train state-of-the-art models
• Training models used in our data processing pipelines, such as classifiers, quality filters, and labeling models
• Designing data curation strategies such as deduplication, quality scoring, labeling, and augmentation that measurably improve model performance
• Creating tooling and infrastructure that lets researchers explore and train on massive datasets quickly and reliably

Skills

• Enthusiastic engineers who can showcase solving impressively hard problems with artifacts such as past projects, designs, or GitHub contributions
• Experience building data-intensive systems, ideally in support of machine learning training pipelines
• Strong engineering skills in distributed data processing at scale (e.g., Kubernetes, or custom pipelines over large datasets)
• The capacity to autonomously evaluate how data quality, composition, and curation affect model outcomes, and to build the tooling to measure it
• Experience building or operating web crawlers

Benefits

• Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.
• Growth paths: countless opportunities to drive impact beyond your immediate role and responsibilities.
• Annual discretionary stipend for professional development.
• Annual discretionary stipend to meet up with colleagues each year, however you choose.
• Annual company offsite, with the team brought together in a new location each year.
• Monthly co-working stipend if you’re not located near one of the main hubs.
• Remote work, executable globally, with the option to work from the London, New York, San Francisco, or Warsaw offices.

Company Overview