Requirements

• 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.

Bonus: Experience building or operating web crawlers.

About the role

• 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.

What we offer

• 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: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities.
• Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.
• Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.
• Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy.
• Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.

Location

• This role is remote and can be executed globally. If you prefer, you can work from our offices in London, New York, San Francisco, and Warsaw.